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#ModernDataMasters: Michele Chambers, AWS

michele chambers aws mdm

Kate Tickner, Reltio

michele chambers aws modern data masterMichele Chambers is a Leader of Product Management and Software Development at Amazon Web Services in Seattle. She has a proven track record in launching new lines of high-tech businesses (hardware and software) successfully and in creating visions and strategic plans for her teams to profitably execute upon. Michele is also a speaker, author and evangelist for the use of analytics to drive better business decision-making.

What was your route into technology, data and analytics?

I grew up in St. Croix in the Virgin Islands and was always very good at math. I loved solving puzzles – and my father encouraged me to challenge myself – but I didn’t have my first science class until we moved to the United States and I went to high-school. In school, I was fine if I could translate a science assignment into a formula or mathematics equation but I struggled with the language barrier at first. I soon got over that, though, and became much better at science with time.

I started out in research and development (R&D) in computer engineering and moved into large-scale applications development at Oracle,  where I cut my teeth on data and business intelligence (BI)-style analytics. The term “BI” had not been officially been coined as yet at that time, but there was a lot of summing, counting, and reporting nonetheless. I then worked on a large-scale BI project at Coca-Cola, which was where I really started to understand the importance of analytics.

I then moved to a consultancy that specialised in analytics, and deriving new insights and discoveries and formulating the data into actions. Our clients could automate these to continually improve their processes and their top-line, or make decisions that would significantly change the trajectory of their organisation. That company became part of Netezza, whereI saw the power of taking that type of analytics and putting it into large organisations at scale. That’s when things really start to take off in a business sense.

I wake every morning excited about the problems or challenges I am going to solve that day – it’s always been a pattern for me. My work life is so much fun because I’m still solving puzzles and having fun doing it just like I did as a child. I am very lucky to love what I do.

How would you define “modern” data management and the connection between that and business analytics?

To me, modern data management is about flexibility and fluidity. The earlier models made things somewhat rigid and difficult to adapt existing technology to a  business as it moved and evolved. Business moved faster than our ability to change the technology based on these relational database models. Now businesses are acquiring as much data as they can, trying to exploit it to drive innovation and new customer experiences.

You need flexibility and fluidity because the landscape is constantly shifting around you. That’s where cloud comes in because it provides the ultimate flexibility – as your business shifts, your infrastructure shifts easily with it.

Today, a business might need to store transactional data cost-effectively, and that’s no problem, but tomorrow you might need to store huge volumes of sensor data. Businesses  need for that to not be a problem either, and certainly not for it to be an 18-month project. They want to get there at a click of a button. At another time, that business might need cold storage for PII data for the last 20 years – you need to access it, but not pay for storage at a premium level.   

That’s what businesses are looking for – a big red easy button to help them change their data paradigm. For me, modern data management is about technology giving you the power to change the way your business is moving and with the same fluidity.

Advanced analytics, or artificial intelligence (AI), still has a ways to go. People don’t really understand it yet in terms of its application to business. They keep doing the same things and expecting different results – this is where there is a big gap.

“Many people tell you to start with the data and then think about what problems to solve – I think that is the tail wagging the dog.”

Start with the complex problems you want to solve in your business. Then look at the data to see if it is the right data to solve the problem at hand, or if you need to infuse it with new data sources to help derive new information. Or perhaps you need to synthesise the data based on your best guesses, allowing you to create simulations that can be evaluated and used to drive new value. This is something I don’t see many people doing in the market today. When it is done, the benefits are enormous – discovering new products, opening new markets, and deriving orders of magnitude in cost savings.

That’s what can happen when you leverage advanced analytics, AI, or business analytics – whatever you want to call it. You have to start with the business problem.

What are your top 3 tips or resources to share for aspiring modern data masters?

  1. Know what you are trying to solve and use the data to inform and shape your solution.
  2. Combine and use your data in new and different ways. If you keep doing the same things with the same data you will get the same results and everyone wants new results.
  3. You have to infuse your data with new data – use behavioural and operational data together for example – if you want new insights.

You have a lot of experience and success in product management in the data space– can you tell us about a time when you have engaged with business users to successfully drive new product innovations and what the outcomes were?

A number of years ago I did a project for that was all about harnessing AI. The company we did it for asked us to come up with recommendations about how to apply AI to their business. I did my research, learned about their business, and worked with them to uncover over a hundred possible solutions that would drive immense value for them. They were completely hooked because we worked out a rough-cut return on investment (ROI) based on interviews with their people about the main pain points in their value chain.

We asked, “What is it about your business that would be of value if you could know it today rather than in six months down the line?” We discovered all kinds of ways to use data and AI to solve all these really complex business problems.

Much of what people are doing today with AI are point-solutions – they are not about entire ecosystems. I always use supply-chain as the example of where advanced analytics and data have already been really successful, but nobody talks about it that way. Supply-chain is all about complex interrelated processes where decisions up-stream drive activities and consequences down-stream. You have to understand how they are connected so you can minimise or maximise down-stream impact appropriately.

What we did for this company was come up with a portfolio of solutions by understanding the entire ecosystem and how the point-solutions could work together. It all came out of applying business understanding to data and analytics, and they decided to go ahead with the top ten suggestions. That’s the piece that technical people forget – to join the dots between the analytics and its practical application in the business.

When Drew Conway coined the term “data science” he said you needed maths and computer science expertise – and there is a shortage of people with those skills – but the real gap is in the third area he identified which is domain expertise – understanding a business and its problems.

What trends or changes do you predict to the data management arena in the next few years?

The two I really see are:

  1. Edge-based cloud computing – Businesses will get to the point where they want really real-time results, requiring a shift to this type of system. You can think about this as a huge network where the cloud will be not merely centralised, but truly distributed right down to small environments. Even your local 7-11 store could rent out floor space for machines to their nearest cloud provider!
  2. Intelligent micro-services – This is so that people can create bigger and bigger intelligent applications.

Blockchain is also really exciting, and a basic component in edge-based computing. I think what blockchain is really about is creating a trusted network for sharing high-value information.

What would you say to young women about whether they should consider roles in technology or data management as a career and the opportunities available to them?

I always tell young women that if they love challenges or solving puzzles then there is lots of opportunity for them in this field.

‘You can go as far as you want to – there are no limitations – there are no barriers. The tech industry is broad and as you move through life you can adapt your career to where you are in your life at that time.”

This is a career where you can build deep friendships and your career can change and develop with you – you don’t have to leave it behind.

What do you like to do outside of work?

I have so many interests. I love art – especially art history – and to travel. I’m an avid reader, I knit, scuba dive, walk the dog, and lots more. I like to cook and eat too much – it’s very varied!

Which is your favourite fiction book, programme or film and why?

My absolute favourite movie is a Robin Williams movie called “Where Dreams May Come.” First off it stars Robin Williams, and he was a genius. But it is also a very visually interesting movie. It’s like a piece of art that merges surreal images with real life and it is very thought-provoking.

“It challenged me to get out of my comfort zone in terms of how I viewed life and death – and I like to be challenged.”

michele chambers asw publications

#ModernDataMasters: Steve Whiting, Chief Operations Officer

Kate Tickner, Reltio

steve whiting coo agile solutionsSteve Whiting is the COO of Agile Solutions (GB) Ltd, a specialist data management and analytics consultancy that focuses on tangible business benefits. He believes in an agile approach to data-driven solutions and co-founded Agile Solutions in 2014 to deliver that vision.

How did you get into data management and what drove you to set up a data management company?

I started on a graduate trainee scheme that Abbey National (Santander) were running in computer programming. I was trained in Oracle relational databases and GUI tools to deliver group-wide Banking Systems. I stayed for a few years and then became tempted by the opportunity to broaden my horizons by becoming a freelancer. I worked in several Telcos and latterly in the City for an international insurance company. I enhanced my skills by becoming involved in new technologies like Informatica in the Data Integration space. I eventually came to join Agile in its former guise moving from Consulting into Sales where I met my future business partner and Agile’s current CEO, Owen Lewis.

Our combined experience of working with other large companies and systems integrators included seeing many examples of failed projects that were not delivering value. We set up Agile specifically to deliver on our promises to customers in the data space, with intelligent digital disruption and proven customer success at our core.

“I think the real way to deliver success involves always acting in the customer’s best interest – keep that at heart and you’ll also have set the right foundations for your business to succeed.”

It’s all about stakeholder management and engagement; delivering on your promises and strengthening the foundations between IT and the business – that’s where we come in.

As COO, I lead the senior management team and am able to steer all the business functions within Agile. I am responsible for making sure:

  • We anticipate and proactively prevent any delivery challenges.
  • We always deliver for the customer, irrespective of the effort required.
  • That the functions in the business pull together to achieve the shared vision for the company.

How would you define “modern” data management and what does it /should it mean for organisations that adopt it?

When we set Agile up in 2014 we had a small selection of spreadsheet-based systems and processes. Over the last 5 years I have set about making sure we are born in the cloud. I confess that a few spreadsheets remain but almost the whole of our business is supported by around 25 cloud-based SaaS systems, including those based on graph database technology. I did not want the overhead of infrastructure and we believe in best of breed technology underpinned by an intelligent integration platform. Our internal DataOps project is bringing this all together to help us achieve greater success and support data-driven decision-making and analytics. The concepts and implementations are what I would define as modern data management.

“For me modern data management is all about agility, scalability and ethics.”

For example, if you show you can act in an ethical way, both in respect to data and by giving something back to the client, then you are well-positioned to be given a broader remit to innovate and scale at speed.

“Ethical data management means you need data governance and data security by design – these initiatives are hard to retrofit. In the past organisations often mobilized for large MDM programmes and had to retrospectively drive the governance throughout – now we are seeing that data governance is often leading – it has become a non-negotiable.”

Especially in the Big Data age, you have to know where your data comes from, what it is used for, what security measures are applied to it but also what its value is to the business.

“You have to be able to tangibly link initiatives to operational cost savings or benefits such as additional revenue opportunities.”

What aspects of modern data management solutions does Agile Solutions focus on and how do you help your clients deliver them?

By design, we are a continuously evolving company so some of the direction we are taking is influenced by our customers and what we’re seeing in the market. Although, we deliver across the full spectrum of what is broadly known as Information Management & Analytics, we see ourselves as different for four reasons:

  • Architecture: We advise on selecting the best-of-breed technology, architecture and tooling to support the business. We are not big believers in monolithic ERP implementations which we often see constrain businesses because they never deliver fully in each area and can become so engrained that businesses become shackled by them.
  • The right people: technically-certified, experienced, business-facing consultants who can be co-located with the business, can speak their language and can add value quickly. We focus on recruiting those people and building them over time using our Agile Academy career paths and development tracks.
  • Delivery methodology: you can guess by our name! Agile, iterative, continuous improvement, deployment etc, etc, all adding value. That’s not always pure agile – it usually needs to fit into existing customer frameworks.

“Our customers typically have roadmaps and programme management frameworks but need to embed Agile methodologies and principles within projects to prove value quickly. We advocate a hybrid approach to this – to support planning and forecasting – while also ensuring strong governance and business agility.”

  • Accelerators: once the foundations above are in-place, we then work with our clients to build and drive use of accelerators, for example to speed up data integration or data quality. We most effectively drive customer success when we engage collaboratively between IT and the business and when we focus on aspects of modern data management within our AIM (Agile Information Management) Framework.

What are your top 3 tips or resources to share for aspiring modern data masters?

  1. Understand the DataOps movement which is about democratizing data and enabling everyone to use data to support their instincts and drive their decisions rather than just data in and of itself.
  2. Surround yourself with other aspiring data masters who understand the value of what data can bring to an organisation so you are not having to continually “sell it” all the time. If you’ve got people who already have an understanding of data and relevant skills, then you’ll accelerate your success.
  3. Always be learning about new technology and trends like Big Data, Cloud, Open Source, AI, ML, Graph, DevOps, DataOps, etc. Technology is evolving so fast that if you don’t keep up you will be left behind.

How important is experience versus willingness-to-innovate for a modern data master?

Experience comes over time but the willingness to innovate needs to be inherent in people. Proactivity, innovation, creativity – you can’t develop those things in people but you can bolster the latter two with experience. You can also help to create experience for individuals; provide a mixture of client engagements and develop their maturity, skills and gravitas to further drive their innovative side.

The other thing to say is that modern data masters need to be leaders who should have a voracious appetite for learning and innovation. For example, as a leader in Agile, I continually read books and apply my learnings to improving the Company. In fact, many of the strategic initiatives which I have driven in Agile have roots in some of the most influential business and technology books that I’ve read.

What trends or changes do you predict to the data management arena in the next few years?

I can see the market heading in potentially four different directions, whereby organisations would typically buy either:

  1. A plug-and-play platform of integrated GUI tools and technologies.
  2. A number of best of breed GUI-driven technologies that are woven together.
  3. The capability to reinvent and redesign using high levels of custom-coded open-source technologies.
  4. Service-based business & technology enablers such as IaaS / IPaaS (Integration as a Service), DQaaS (Data Quality as a Service), DMaaS (Data Migration as a Service) etc.

The first three are already established to varying degrees but the latter is supported by the ongoing trend of cloud and smart infrastructure supporting these “service-based” initiatives. For example, look at Lyft’s IPO – they see a future where you no longer need to own a product to enjoy its benefits and where users simply leverage a comparative service instead.  This service mentality is starting to welcome a new incarnation of SOA-type architecture which is fueled by Cloud platforms such as Google Cloud, Amazon Web Services and Microsoft Azure.

There are other things specific to master data management. Executive sponsors no longer want multi-year, large, heavy MDM deliveries. They want speed and the ability to evolve. They are looking beyond “single view” to see how they will use it to get better analytics and intelligence around a customer or employee or which products will sell or not sell. It’s much more about multi-domain and relationships now as well. With this focus on relationships, NoSQL and graph databases are well- placed to become more dominant in standard enterprises because they can vastly extend the number of potential use-cases
How well placed is Agile Solutions to continue to grow based on these trends/changes?

“It’s more about a state of mind. We recognise that there is never an endpoint in evolving a company – you’ve always got to be innovative and grow and scale to keep ahead of trends and developments in the market.”

It’s a journey which we’ve embraced through the implementation of communities within our organisation.  Each community is aligned to trends that we see in the market such as Data Engineering, MDM, Cloud etc and they allow us to evolve and grow (or shrink) in-line with the wider technology market.

What do you like to do outside of work?

I love spending time with the family as long as the kids aren’t arguing!  I’ve got a wife, two children, no pets and a place in Spain where we all love to go. I also have a passion for cars but recently with my emergence into mid-life, I’m reminded how lucky I am to have my health and a wide family.

“My health particularly has been boosted recently.  For every one of the last five years I had the same goal to lose weight but over the last 9 months, I knuckled down and made a conscious effort to keep fit instead of keeping fat!  And in April, I managed to run the equivalent of 5 marathons in aid of charity. What’s helped to drive me on is access to all the data and the gadgets that enabled me to monitor my progress, keep on track and ultimately get back into a pair of 32-inch waist Levis!”

Which is your favourite (science)fiction book, programme or film and why?I’ve got an interest in film spanning back to the advent of DVDs and

I’ve got a favourite book but it may be a bit boring to share! It’s called “Managing a Professional Services Firm” by David Maister. There are several other business book favourites of mine including “The Lean Startup”, “Shoe Dog”, “The Upstarts”, and “The Pumpkin Plan”. I take inspiration from them all as they have helped me to develop Agile Solutions into the company it is today.

Do you read any fiction or watch any films or TV?

“I have a confession – I’m generally either working on the business, thinking about the business or reading books about business. The only way I switch off completely, apart from family time and box-sets, is to watch total rubbish on the TV!  Don’t tell anyone but several of the shows I’m interested in are the ones that run over the summer period which remind me of being much younger than I am now!” (laughs).


steve whiting agile coo

#ModernDataMasters: Bob More, SVP Global Field Operations

modern data master bob more svp global field operations

Kate Tickner, Reltio

    modern data master bob more svp global field operationsBob More is Reltio’s SVP Global Field Operations and responsible for all aspects of business development, alliances and partner support.

    What is your background and what was your route into data management?

    I’ve been in enterprise sales and sales management for just over 20 years now – mostly on the business application side of the house including numerous early stage start ups and the big household names like IBM and SAP. Much of background is what we now call customer experience and its predecessors of CRM and eCommerce applications in Retail and CPG as well as PLM, ERP and supply chain.

    Despite the hype the key to success in these areas has always required reliable data to make the systems work properly – and that was a challenge for all of them too – so we as sales and customer success (before they had a name for it) people lived and breathed all the data problems. As an applications vendor we typically overlooked or never really had a solution for the data challenges other than to tell the customer that they have been running their enterprise successfully on this same data so just put it all in our application – which never really worked too well!

    My first introduction to MDM was at SAP where I had to explain to CEO’s why they had to buy another software module from us just to make their “Holy Grail” fully integrated enterprise platform work as advertised.  Having experienced similar challenges living through the “.com” bubble of the late 90’s with the onset of omni-channel initiatives it seemed obvious that none of the application vendors were addressing the data or the fuel that ran their solutions.  This was the primary driver for joining the team at Siperian who at the time were a leader in the first-generation MDM space.   

    “Coming from a pure apps background, we all knew of MDM but did not have an infrastructure sales background.  Whether through a stroke of brilliance or more likely a dose of good luck, we adopted what we knew best and we sold MDM in the same way we had been selling applications – we took “plumbing” and sold it to the business making it required enabler of any LOB kind of initiative.”

    As a result of the highly visible and mission critical solutions we were providing and the ongoing industry consolidation, Informatica acquired Siperian in 2010 and it has since become the cornerstone of their MDM capabilities. I met the future founders of Reltio at Siperian and Informatica so when they got Reltio out of the garage and into a couple of real customers, I was recruited to join a number of my former teammates and joined Reltio in 2014.

    Why did you choose a Sales job originally?

    Being in control of your own destiny was key – certainly there’s a financial element of it – but I thought that it was a great opportunity to learn a lot and move around an organisation. My Dad worked for Honeywell computer for 35 years so I grew up in the IT  world. In college I did some co-op internships in Honeywell’s marketing department. One of my of my first co-op jobs was cleaning up all of their customer installations address and contact data files. These were physical addresses of where their systems were installed and were all printed out on reams of green-bar computer paper.  .

    “It was piles of paper, a ruler, a highlighter and a pen – manually writing out which ones should be combined and which ones should be struck out. So I was manually doing data cleansing and merging – I was doing MDM way back in college!”

    How would you define “modern” data management and what does it /should it mean for organisations that adopt it?

    Well MDM has evolved a bit from the paper, ruler, pen stage! There was the first-generation stuff that we were doing in Siperian, to what we do here which is modern data management. It delivers a number of things and some of the most important ones are:

    • Faster time to market through a much more agile architecture that allows you to get something up and running quickly to feed the consuming apps and achieve value much more quickly.
    • Enhanced relationship management – not just getting that single view of the customer but unlocking all of the relationships between the customer, the supplier, the project etc. Being able to find and visualise all these things.

    “Companies have spent trillions on applications and technology over the years and have really not given data its due. Most of these projects fail or are sub-optimal because of poor data.”

    When we talk to our clients about Reltio and what modern data management means to them, we find out that they are optimising the value that data can bring to their organisation:

    “It’s something that helps them build new business models where companies can quickly monetise their data and launch new corporate innovations on an agile, extensible platform.”

    What have you learned about MDM that you’d like to share with aspiring modern data masters?

    I’ve seen it most successful when it’s taken in the context of a larger overall initiative, for example a digital transformation or implementation of a new system or process. In these cases there is a whole strategy behind it which goes beyond the data and is about the applications; integration and process change.

    “Usually a larger corporate initiative is going on and we are just one critical part of it – these programs tend to be more successful because there is more likely to be a well thought out script of what role the data will play in it.”

    These initiatives are typically highly visible in organisations; the funding is sufficient and more certain and they have executive and LOB sponsorship. Most importantly there is a level or urgency involved in evolving the solution.  That’s where I’ve seen the more successful projects deliver the most value.

    “The solely IT-driven ones are more likely to be a plumbing exercise – more about pulling data together and feeding it somewhere else. They can be successful but more often than not they don’t realise the business value of what they are doing because it wasn’t made clear at the start.  The good news is that the days of such science projects are quickly going away as broader transformational programs become the norm”

    What is it about the partners that have adopted Reltio and “modern data management” whole-heartedly that makes them different to some of the laggards?

    “The fact that our partners have jumped on the band-wagon sooner than others tells you they are probably a bit more progressive in their thinking about how to leverage data.”

    They’ve got the battle scars of the older, legacy approach to MDM and just like their customer they are looking for a better, more modern way to address these problems.

    “They are more forward-thinking themselves so they are probably being great thought leaders for their customers, bringing new ways to do things.”

    They probably also have a good understanding of the peripheral technologies – ETL, DQ and other things like the DW for example Snowflake – so they’ve got a good understanding of other contemporary architectures that are leveraged and enhanced by Reltio.

    The fact that they are recommending something that will be implemented faster and therefore bring faster time to value is quite enlightened of them because they do have a choice in the MDM vendor space. There’s a dichotomy – drive more hours of billable time on low margin commodity work OR fewer hours of higher value advisory, strategy and differentiated services.

    “This demonstrates their credibility from a thought leadership perspective and frees up more budget for the client to spend on more impactful areas. Whatever they can do to get something up and running faster will bring value to their customers.”

    They can bring in Reltio and enable many more down-stream applications, Getting the master data delivered quickly means more value and many more projects later. They then have the trust and credentials to win more of their customers’ business so they can build and maintain long-term relationships.

    Apart from customer/product 360 or regulatory compliance type use-cases how do you see modern data management being used in businesses over the next 3-5 years?

    One trend is the move to cloud which seems fairly intuitive to us at Reltio but in the MDM space it really hasn’t happened full force yet. Only a very small proportion of the market is doing it yet but the analysts believe it will be the focus.

    “We have the distinction of being the fastest-growing cloud vendor in the cloud space. That drives a lot of opportunity because many of the application data sources are now in the cloud and clients want to manage it in the cloud.”

    Data privacy is coming up more and more beyond just GDPR. Many more regulations are being adopted as consumers demand full accountability – less “creepiness” if you will! Data morality and ethics are definitely areas that need to be grappled with and data management solutions like Reltio and others like e-discovery tools will be front and centre in that trend.

    Use cases like M&A are coming up more and more – we are seeing companies using our solution to facilitate a faster transition by bringing their data together especially in Life Sciences right now. That is not a typical MDM use case but of course the faster they can join the businesses together the faster they can realise the joint benefit.

    Migration of systems. CEP systems and core ERP are moving off legacy architectures or previous versions and moving to the latest and greatest versions. The ability to do that quicker and ensure better data quality in the process is a critical use case where we are starting to see some trends emerge.

    “These migrations take far too long; they are over budget and under delivered. Anything you can do to speed that up and facilitate that is significant.”

    Also the ability to manage the data outside of the core ERP systems which the ERP systems really don’t do a great job of – these are all perfect ways for systems like ours to augment that experience.

    What do you like to do outside of work?

    If you have been around me for five minutes you will quickly know that I am a diehard l New England Patriots fan.  Growing up outside of Boston this has become an obsession along with the other Boston sports teams. Other than that, and work, I don’t really have much time to do anything except chase my kids around! My wife and I spend much our time at College Football games (for my son) and competitive horse shows (for my daughter) – kinda being Dad.

    What is your favourite book, film or programme?

    I’d say one of my favourite films of all time is “The Right Stuff” which is about the Mercury 7 astronauts based on Tom Wolfe’s book. It’s a great movie, it chronicles the human elements behind the space race of the 1960’s. This period was an amazing time in history.

    “It pulled the whole country together in a common pursuit that was important and prideful and could show what could get done with teamwork and dedication – as well as a whole lot of life and death risk.

    I don’t know, I guess I’ve always just wanted to be an astronaut!”

    modern data master bob more the right stuff

    #ModernDataMasters: Martin Squires, The Analysis Foundry

    Kate Tickner, Reltio

      Martin Squires modern data master martin squiresis a leader with extensive experience in customer insight, marketing analytics & data science. He has had senior roles with organisations that include: M&S Money, Walgreens Boots Alliance, HomeServe and Bradford & Bingley. Selected for the last 5 years as a member of the Data IQ Data 100, Martin has considerable experience helping organisations drive value from building a deeper understanding of their customers.

      What was your route into technology, data and analytics?

      I always liked maths and stats as a kid – I was then, and still am, very happy buried in a book of football statistics! I did an economics degree and then around three years in production planning and logistics types roles before starting as a junior economist for the old National and Provincial (N&P) Building Society.

      “In terms of data and analytics it all started when I sneezed and slipped a disc shaving would you believe?”

      It was the early 90s and I was working on the analytics and forecasting side of things at the N&P. When I hurt my back I was off work for about 6 weeks. On my return I was offered, and I accepted, a role on a project about customer data and segmentation. Four weeks later I asked if I could stay with that project because it was a lot more interesting to me than economics!

      How would you define “modern” data management and the connection between that and business analytics?

      It’s the classic garbage in garbage out, but it is even more important now as we move into the real drive towards machine learning and artificial intelligence. Fortunately more people today are taking data management seriously than 30 years ago – even if it is still regarded as a necessary evil by some.  Particularly the data governance side is beginning to be seen as really important.

      If I look back to building models 15-20 years ago, the human statistician was more in control – a decent statistician could certainly examine a model and be able to find any bad data.

      “As we move into a more automated age – where things are delivered by black-box techniques, deep learning and AI – it is even more important for the data to be correct because otherwise it will impact the customer experience. If you don’t get the underlying master data right then all the AI and ML techniques will let you do is get things wrong faster!”

      There is now a growing acceptance as well that cloud is not “evil” – much more acceptance of that and open source as well. Things are becoming more flexible and the challenge now is probably that there is lots of technology tools around and they have over-lapping functionality. It is difficult for people to keep track of what they are trying to deliver because of all the different technologies they have to choose from.

      What are your top 3 tips or resources to share for aspiring modern data masters?

      1. Data strategy shouldn’t be separate from business strategy and it must be fed from that. People still tend to regard data strategy as a silver bullet – they think you just need to build a data lake and everything will be ok. For me it doesn’t work that way – know what you want to deliver as a business and then decide on the data and analytics to support that strategy.
      2. Keep the focus on the value you want to deliver via that business strategy. Don’t get distracted by the tools and shiny new technology toys. If simple technology will do then use simple technology.
      3. Keep learning. One of the things I love about what I do is that nothing stands still.

      “There are always changes on the technology side but also on the use case as well. You need to stay informed and build on your knowledge and expertise and also understand what other people are doing.”

      You have a lot of experience and success in analytics of all types to drive deeper customer insights – can you tell us about a time when you have engaged with business users to successfully derive and apply new insights and what the outcomes were?

      One example is a project I did at Boots who are famous for 3-for-2 promotions. We had one which is a good example of something I really believe in which is that you need to get out into the stores and not just sit in front of a computer. We had a promotion of 3- for-2 on a particular type of nappies which was only working in some, but not all of the stores. To find out more we needed to make a field trip.

      We went into one of our large stores in Nottingham and what we saw was a young mum with a child in a buggy. She went to the nappies, put one packet in the buggy, gave one to the child to hold and put another under her arm before paying and leaving the store to go to a bus stop. We approached her and helped her onto the bus – having shown our badges so she knew we were Boots employees! We then went for a coffee and had a chat and we realised that what we should have been considering was how someone could get 3 packets of nappies home if they didn’t have a car.

      “When we went back to the office and overlaid car park location data we then had an “ah hah” moment because the promotion only worked where there was a car park nearby. So you’ve always got to factor in all sorts of things that are never going to be neatly stored in a database.”

      Then think about other ways to get around the problem – may be run the promotion on line with free delivery for example.

      What do you think are the essential skills to be a good analyst?

      “I still thing the four biggest skills are creativity, curiosity, communication and common sense – if you’ve got those then you can be taught technical skills.”

      If you haven’t got the imagination to look at the data and almost forensically solve the mystery then you won’t make the best analyst. Just like in the TV programmes like CSI where the analysts solve crimes by a combination of analysis and field work, there is no better way of understanding what is going on than going into the real-world for example visiting shops or listening into call-centre conversations.

      I remember years ago I sat in a mortgage call-centre and watched the reps tab through the non-compulsory data fields. They were selecting option 1 every time because they were targeted on speed per call and not on data quality.

      “You only learn that kind of thing by getting out of the office. You’ve got to build your experience and remember that if anything in the data looks too good to be true then it probably is!”

      The industry makes itself seem more complicated than it is even at the recruitment stage. We put people off and make them think they need a MSc in stats or Computer Science. If you are curious about data then there are plenty of roles for you.

      “Some roles do require a PhD but mostly you just need that forensic interest in solving the problem – curiosity is much more important than loads of qualifications.”

      Could you also please share an example of where things have not gone so well and what you learned from the experience?

      There are plenty of those and many of them relate back to the previous example of needing to understand the business context and real-life situation. For example as a young analyst at N&P I built a model for Home and Contents Insurance in order to better understand our retention strategies. I was really excited because I was looking at the key variables and found a real link between clients closing their mortgage and closing their insurance policy. I went to tell my manager all about my latest discovery and he said “well they would do because we can’t sell insurance separately so if they close the mortgage then we automatically close the insurance policy!”

      “Most of the things that have gone less well have been to do with not spotting errors in the data or not spending enough time getting the brief right up front.

      You might be asked a question but you learn over the years to drill into a bit more because a request for a “simple” piece of analysis is very often not straightforward. You need to understand the context and the big picture about what is driving the request so you can decide what analysis is really going to help.

      What trends or changes do you predict to the data management and analytics arena in the next few years?

      I think some of the consolidation in the industry is really interesting – for example the Salesforce acquisition of Tableau – and that there is a lot more consolidation still to come. I think this is generally going to be a good thing long term in terms of simplicity even if it means a bit of short-term pain for customers – with any merger they often end up with 2-3 account managers coming to see them instead of one!

      I think there will also continue to be a drive to improve BI capabilities and also their useability for non-technical people. That can be a double-edged sword because I think you still need to have a certain statistical knowledge to use some of these things.

      “As NLP gets better we may be able to have a conversation with a computer and have it decide how to do the analysis we need. It would be interesting to know how far we are from the Star Trek computer!”

      What do you like to do outside of work?

      The stats addiction still comes through a little bit and I probably take Fantasy Football a little bit more seriously than I should do! I managed to win one of the mini-leagues I was involved in last year.

      “Stick me in front of any science-fiction movie and I’m generally happy. I love sitting watching things like the Walking Dead with my kids – don’t worry they are in their twenties now so it’s fine!”

      I particularly like Neil Gaiman and so I am currently binge-watching Good Omens and a favourite book is Neverwhere. It’s just a brilliant mix of fantasy and real-world locations – it’s very difficult to get on a Tube in London and think about it in the same way if you’ve read that!

      What’s next for your career?

      I haven’t decided yet as I’m lucky enough to be in the position to consider my next move carefully.

      “If there are organisations out there who want someone that will build their team, get their data right and get s*** done then I’m open to having a chat!”

       

      mdm martin squires founder the analysis foundry

      #ModernDataMasters: Henrik Liliendahl, Chairman & CTO, Product Data Lake

      Kate Tickner, Reltio

        Henrik Liliendahl is an MDM and PIM expert; speaker and blogger (www.liliendahl.com and https://mdmlist.com/category/the-list/) and the Co-Founder, Chairman and CTO of Product Data Lake a product information exchange service. He has many years of cross-industry experience in consulting with clients across all major MDM and PIM technologies.

        What was your route into technology, MDM and PIM?

        I got good grades in mathematics at school but it was an evening class in secondary school that I took in what was then called EDP (Electronic Data Processing) that got me started. We didn’t even have a computer at that school so the whole class was about things drawn on the blackboard. Then one day we had a trip to a larger college that actually had computers and I was hooked!

        I was educated in computer engineering but my first job was on the business side. Since then I’ve bounced back and forth between IT and business. In the late 1990s I got into data matching and developed some algorithms myself because the internet was not as good then or I probably could have found some online.

        “The situation was that two companies wanted to merge and wanted to know if they had customers in common. To find that out we applied some matching techniques.”

        I developed that product and later merged it into a larger company. But that was my route into data management and going from there into MDM PIM and data governance. Now I think I have a good coverage of all the different disciplines.

        How would you define “modern” data management and what does it /should it mean for organisations that adopt it?

        Getting a more holistic view on data. Looking at data enterprise-wide has always been part of MDM but modern needs mean you must now look across companies and business ecosystems.

        “Driven by digital transformation, companies must interact more and share data – they cannot reinvent the wheel, they need to work together. Business ecosystems are surely a part of modern data management.”

        Embracing different data stores in the technology space. Entity relationship databases have ruled the world for thirty years or so but now we are seeing datastores that are not that rigid, and data lakes coming in. Lots of different types of databases – graph, document databases that can all be used for different purposes and we need to embrace those.

        Also of course deployment in the cloud is the thing in modern data management – we will stop running all of this on our own iron and get it from someone else.

        “Cloud gives more agility in deploying and new ways of handling data. Funding is also easier because it is subscription and the funding corresponds to your usage.”

        Also DaaS. I remember back in the old days if the postcode table changed in your system you used to have to get a new postcode table and put that back into all of your services. Now with DaaS you have this kind of data in real time – not just postcodes but all sorts of reference data and many other third-party data sources available immediately in new applications. That’s a huge advantage.

        What are your top 3 tips or resources to share for aspiring modern data masters?

        1. Find ways not to manually type in the data – try and find data that is already digitalised. You get so many errors when people try and type it in themselves.  Get it from outside which is already out there and is refined.
        2. Connect instead of collect. Don’t harvest all data yourself – get it externally where it is already collected and maintained. You can find third and second-party data – you don’t always need to be collecting it internally.
        3. Data models – look at the real world. Eg a customer table. Yes you have customers but does your definition of customer make sense in the real world? Often a customer is also another entity at the same time, such as a person/organisation/supplier/employer as well.

        “Try and model the real world into your data stores because then you are prepared for future use cases. That is often something that goes wrong – you make your model or application according to how your business looks today and then in two years you have to scrap everything.”

        However if you look at the real world and think about what might come then you will be better prepared and can probably re-use your data later in new business models.

        You have a lot of experience and success particularly in product-related data. Can you tell us a little more about the concepts behind Product Data Lake and your vision for how it could be used in the future?

        It is based on the theme of business ecosystems and products flowing easily between trading partners. Product data looks very different depending on the product you are talking about and manufacturers see products very differently from the merchants.

        “On the technology side you can exploit cloud services and data lake concepts which means you can receive the data in the form that say, a manufacturer might submit it, but consume it in a way that a merchant might want to.”

        We do the linking, matching and merging inside the data lake at the time of consumption. We also start to use AI in doing this linking and mapping and transformation – it’s a huge task in terms of the data that flows through and very complex because it is not just one organisation but many. We are at the crawl stage at doing this now but we are aiming to walk then run!

        It is also a bit like social media in terms of linking. That is, trading partners request and accept partnerships like you would do in a social network. We are also using tagging of data to help with the linking and consumption of data – as you do in social networks. Really using and embracing these concepts that are out there in terms of collaboration. We also like to collaborate with suppliers of similar technologies like Reltio and others out there on the market.

        “It is a bit like an advanced Dropbox where the manufacturers drop their data in and the merchants take it out. In the middle we do all the matching and linking and provide the infrastructure that the algorithms or exchange gateways run on.”

        Could you also please share an example of where things have not gone so well and what you learned from the experience?

        I always like to collaborate and that is a great thing of course but only if you align expectations. You need to be sure that you have the same expectations – not that you have to write a 30-page legal contract – but that you talk through success criteria and what each of you consider to be a win-win. I missed that a few times and hope I will not do that in the future.

        It may be that some highly technical people are sometimes not great at talking but probably more because in these projects you mix technical and commercial people. Aligning these two worlds is difficult and what one side thinks is obvious is not obvious to the other side. Make sure that you are not making assumptions about other people’s understanding.

        “As far as specific examples go, I could share a few stories but it’s probably better if I don’t! (Laughs)”

        What trends or changes do you predict to the data management arena in the next few years?

        We talked about business ecosystems and I really think that will increase in the future. We also touched on AI which is another buzz word but one that I think will be more sustainable than others have been. I think it will have huge growth and have a great impact on what we do in the future. We could also talk about the Internet of Things – we will see more and more smart devices, not just phones but refrigerators and drilling machines and of course lots of smarter industrial machines. We will see scope-creep from IoT into data management – it will have a huge impact.

        There will be more cross-department and enterprise wide working – companies are increasingly coming up with global rather than local solutions already. This will then spread into the business ecosystems so we will see people working with people who are on the pay roll in other companies or who are contractors. We will see that we will have shifting colleagues and working scenarios around data especially where it is connected to business outcomes.

        Is there anything we have not discussed that you would like to cover?

        No, I think we have covered all my pet hobby horses!

        What do you like to do outside of work?

        I am at an age now where I have grandchildren so I really like to be with them. I like to walk and bicycle – it is good exercise but you can also think while you do these things. It is as much to freshen my mind and do some out-of-the-box thinking.

        I am very interested in history so I like to visit historical places – fortunately I can often combine that with my work so when I travel I try to leave some time for pleasure and to experience different cultures. Things have changed a lot since I was young – it used to be completely different wherever you went but now you have very similar shops on every high street – always an H&M and a Zara. You can tell that I have daughters!

        Which 3 people – living or dead, real or fictional – would you invite to a dinner party and why?

        I said I was very interested in history so it’s probably not surprising that I would pick some historical figures. The first one would be Herodotus – an ancient Greek historian – perhaps the father of history. He was probably the first person who applied a methodology to writing history – he did not just pick the first and best anecdote. Instead he gathered the facts and made an informed decision on what to include.

        Charles Darwin – famous for his theory of survival of the fittest. Modern science has come up with a slightly different theory which is about survival of the fit enough – you don’t always have to be a winner.

        “There’s a clear analogy to MDM in that – the thing about the golden record being the only data to survive is not true – there is more than one version of the truth.”

        It would be good to hear what Charles Darwin thinks of these later theories.

        And with these clever people I think Albert Einstein would be the third one.

        “There are all these quotes on the internet that are attributed to him and it would be good to know what he really said and what he really meant instead of these quotes that we can’t find the source for. That really irritates a data quality practitioner!”

        That sounds great – what are you cooking – can I come too?

        If I am cooking my signature dish is Spanish Paella. And sure, you are welcome.

        blog henrik liliendahl footer image

        #ModernDataMasters: Sarit Bose, Cognizant

        Kate Tickner, Reltio

          Sarit Bose is the Head of Business Analytics and Insights at Cognizant UK&I. He has more than 18 years’ experience in Business Consulting, Business Development, Implementation and Pre-Sales across multiple domains. Sarit is accustomed to working across large enterprises and driving C-Level initiatives.

          What was your route into IT and data management?

          I always loved Maths and Physics as a child at school. I used to save money from my pocket money and gifts. Before I decided to buy anything, I used to calculate the interest I could earn. The love for numbers and computation led me to do statistics and then computer science at college. For me everything was a formula which is why I quickly realised the vital importance of good input data to work with.

          “We all know the “garbage in, garbage out” saying but unless you are working in data management then it is probably hard to gauge just how important it is to get the data right and the impact it can have on the results of your analytics.”

          I learned this very early on and it is even more important in today’s world of big data.

          How would you define “modern” data management and the connection between that and business analytics?

          I see modern data management as a way to bring a method to the madness in terms of this entire data deluge. Until relatively recently it has been considered “normal” to do data management projects which take 6 months, 1 year or longer.

          “I don’t think that in today’s fast-paced world people have the luxury to do a project that takes a year just to get the data right. By that time some of it will have lost its relevance and a new kind of data will have come in.”

          It is very important that you apply a set of modern techniques to get projects done faster. This means doing things better; applying learnings from the past and automating the application of that learning. That is the way I would differentiate between modern and traditional data management.

          In relation to business analytics there are a huge amount of techniques now that have to be applied to deal with complexities which we were not able to do earlier in a traditional mechanism.

          “There were certain limitations of doing things on an RDBMS and traditional storage – for example being dependent on storage, not being able to get the funds to continuously scale up processing, not being able to incorporate macroeconomic and social factors that impact decisions etc. Some of this definitely meant compromising on the quality of things and giving away the opportunity to look at the bigger picture.”

          This is where modern techniques are really helping. Big data is all about being able to store and process data very fast and then the application of analytics and AI /ML just to manage the data – never mind using it for any other business purpose. Analytics today is everywhere – not just at the business end but also at the data management end.

          “You have to continuously apply Machine Learning to learn how you have been treating the data. Then you can treat any new type of data coming in automatically and you are not dependent on any individual brilliance to figure out what to do with it.”

          How important is experience versus willingness-to-innovate for a modern data master?

          It is a combination. Experience plays a large role – human experience as well as the experience of managing of data – so we can leverage what we have learned and apply other techniques on top of it. That’s where innovation comes in – how you continuously evolve and become more and more efficient – make less mistakes in how you are treating data.

          “If you are going to succeed in this game you need to use the combination of both. Experience has to be combined with continuous innovation – that’s the only way forward – nothing less than that.”

          You really have to see what fits in well and what will give a better ROI. You decide whether to apply the human brain or tried and tested techniques as opposed to something new just for the sake of it.

          “If there is no ROI then it probably does not make business sense. Is it solving a problem? Making things easier? Is it a lower cost? Will it make you scalable for the future? If the answers are yes then innovation will make sense, if not then it is innovation for its own sake. At the end of the day, whatever we do has to make business sense.”

          What are your top 3 tips or resources to share for aspiring modern data masters?

          1. Know the objective before you apply the technique. What is the purpose the data is going to serve? Understand and realise what you are trying to do first and then choose the technique. What business are you in? What are people trying to do with the data? What are their pain points?

          “You apply a solution to a problem so you need to know where your goal post is if you want to score a goal or you will be kicking the ball all around the field.”

          1. Pursue perfection: Always be asking how can it be improved? How can it be done faster, deal better with complexity or deliver better outcomes? Use the combination of technology and human experience to solve these problems.
          2. You have to love data: The numbers should dance in front of you and start making sense for you straightaway. There will never be enough documentation or literature to always tell you what the allowable values should be for a particular field. You have to have an eye for it and develop your judgment and use AI to retrieve it for you if you cannot. You must love data and numbers themselves.

          A combination of these three can make somebody very successful.

          You have a lot of experience and success in digital transformation – can you tell us about a project where things did not go so well; what you did to fix this and what you learned from that?

          I have failed many times in my life but I’ve picked myself up and moved on. Each of these failures has taught me something and helped me to improve myself as a human being in general. The same thing applies in work – let’s start with these:

          1. Not knowing what you are trying to solve: Just applying techniques and finally realising that what the business needs and what you have delivered is a wide gap. This is the root cause of many project failures.
          2. Timing is of the essence: When do people need that data? If you have a project plan that takes too long then by the time it is finished the need for it may have vanished and people will have found other ways around it.

          “One reason why many MDM projects have been disbanded in the past is because people cannot wait infinitely for the project to complete. They will figure out a short cut and then what you did is not relevant anymore.”

          1. Be nimble: If you assume your scope of work is watertight and you don’t want to complicate things by change requests, then what you deliver may be on time and in budget, but the deliverable might not be usable. Business needs change fast you need to figure out how to address that within the project. Figure out how to take the customer into your confidence and make them understand that they may need to invest in a change – that’s the way to move ahead.

          “Saying no or hiding behind the scope of work does not pay off – you might be able to deliver a project but a project that does not enable people to change the way things happen is not a successful project. People are not going to remember you for that.”

          What trends or changes do you predict to the data management arena in the next few years?

          IOT is going to become one of the key data sources going forward so data management solutions need to prepare to deal with this right now. Having APIs to deal with it will be very important.

          Blockchain is going to play a big role to giving more trustworthiness to the data.

          “If you are going to create a single version of the truth it needs to be a single version of SECURED truth. It is not evolved to that extent yet, but like AI and ML have evolved, Blockchain is going to become a must.”

          The data space will become AI and ML driven – the way you acquire data, map it, manage it, find unknown relationships, do data lineage, generate insight on the fly and provide it in real time will all be impacted. That is where agility comes into play.

          Is there a question you would like to have been asked?

          Q: As practitioners should we ever be happy with the solutions we are providing?

          A: No. Always ask yourself is this all that I could have done? I think that sometimes we become complacent when we think we are the best without realising that someone else is doing the same thing but better. Once you get a pedestal you are always at risk of losing it because for the others in that space, everything is up for grabs.

          “For each interaction I have I would like to leave an impression and be remembered for any value I delivered. But it cannot be the same kind of value every time – so I have to continuously improve that value – that’s the way to be a great practitioner or a great organisation.”

          What do you like to do outside of work?

          One thing that I love, is a walk in the morning when I do not speak to anyone else. It gives me some time to spend with myself and gives me a lot of energy.

          I also love to people-watch – sometimes I will sit in an airport and just watch people around me – we can become so absorbed in ourselves, our lives, our families that we forget to stop and look around. We lose the broader plot – we stop being human and become more like robots.

          “It’s really important to get out of your routine, spend time with yourself, ask yourself whatever you did yesterday as a family man, as a human being, as an employee? Are you happy?”

          If you are not happy you are not going to last very long and you are just going to drag yourself into things. If you don’t love yourself you can’t expect anyone else to love you!

          Which is your favourite fiction book, programme or film and why?

          I am a book worm. I read anything and everything that comes in my way. I will watch movies if I have time to watch the whole thing because I hate to leave things unfinished.

          One thing I often read is a book from India called Mahabharat. It is a very ancient text -similar to the Iliad and a lot of the aspects that are covered in it:

          “It is fascinating to me that someone wrote a book on family, world politics, science, life lessons, philosophy, so long ago which is so pertinent today. This book helps me look at things with a very different perspective – for example what inspires people to do good or what obsession can lead to. The essence of the story is still very, very relevant today. It’s one book that teaches me something new – every time I read it.”

          mahabharat

          Fast-Track Your Data Monetization

          Ramya Krishnan, Reltio

          This time Janine was beaming.

          I had a pleasant meet last month with Janine, when we had discussed How to get Data on Tap for all Your Data Woes. My old friend was super curious to learn more, as we met again this month for another cup of coffee.

          “So nice to see you, Ramya! Thank you so much for the Data-as-a-Service guidance. We have more or less decided to go for it, and I need you to fill me on more details. Monetizing data – as you had mentioned last time.”

          “It’s a smart way of tapping the potential of your data to create a new revenue source. You’ll wonder why you never thought about it!” I laughed as we sat down. “As you know Janine, DaaS works for streaming data in real-time from anywhere in the world and from any device, delivering consistent data quality and agility. Naturally you pay for accessing the data. Now suppose others pay you for accessing your data?”

          “Oh!”

          “With DaaS, you need not be a data consumer alone, you can be a data provider, too.”

          “That is wonderful!”

          “It is indeed. In the data economy, you have invested so much in creating a great asset, your enterprise data. How about licensing it for use by others? That is Data Monetization put simply.”

          “That sounds really exciting. Being in Pharma, we consume huge volumes of data, but we also generate equally large data.”

          “Trust me, data is the most exciting thing happening today, and it’s high time you participate in monetizing it. Reltio DaaS makes it very easy to fast track your data monetization. You already have quick access to datasets readily available from data tenants in the cloud. You have a single reliable source of data that is continuously updated and refined. Choose one or more from the multiple engagement models we provide, and you are ready to go.  The simplest is the Data Store-front where users can search and browse data, and download by paying.”

          “Sounds amazing!”

          “Another model is List Match Service, a stand-alone service to provide ad hoc matching, enrichment, and validation. You can also consider Data API Services, which are custom services for a particular data domain. For example, HCP credential verification in the Healthcare and Life Sciences vertical where you operate.”

          “Lots of options, more than I had thought.”

          “Yes. Moreover, to help you monetize your data quickly, we have a robust API platform for custom services and embedded experience. In fact, we can help you set up in all four models, including MDM Data Subscription, which is the data delivery to MDM tenants.”

          “Let me discuss with our people which way we should go.”

          “Right. If you choose to go with Reltio, I promise you don’t have to run around as we take care of everything. We help onboard new customers much faster and we can enrich data via list match service. Being integrated with Reltio’s modern and scalable platform for continuous data quality and delivery, you can quickly implement any changes to data. And guess what, we have a convenient pay-as-you-go billing method. As your customers increase, you can also look forward to reducing distribution and operating costs.”

          “So I guess everything is set up!” Janine was happy with the thought of generating revenue from enterprise data. Who wouldn’t be?

          “Just one more point. I suppose complete tracking is part of the service.”

          “It is. You can track attribute level audit, history, and lineage of all data usage and changes. Track record-level and attribute-level consumption patterns. Track a variety of contributing data sources for ongoing updates and downstream data distribution. And you don’t have to worry about strong data security and privacy regulations. Reltio platform is HITRUST CSF-certified, and GDPR compliant.”

          “Very comprehensive and competent. These coffee sessions are turning out to be amazing for me!”

          Like Janine, several customers have benefited from Reltio’s fast-tracked data monetization, extending their quality data to drive revenue for the organizations. How about you?

            #ModernDataMasters: Tony Saldanha, President, Transformant

            Kate Tickner, Reltio

              Tony Saldanha is the President of Transformant and a globally recognized information technology and shared services executive. He has more than 30 years’ experience in industry, including 27 at P&G where he led IT and Global Business Services for every region, and is a champion of creating new, relevant business and technology models to stay ahead of disruptive technology capabilities.

              What was your route into IT and data management?

              I have been in the world of IT for about 33 years now although I was anything but IT or data minded as I was growing up. However, as soon as I entered the workforce it became apparent that the future was IT, technology and data management and that’s when I saw the light!

              I’ve had the great fortune of evolving with the IT and shared service industry across 6 countries and 13 different roles and assignments. I started the first shared services centre in the Philippines in 1993 and then was also involved with major outsourcing at P&G in 2003. Also, I was CIO of Gilette when P&G acquired them and then had the opportunity to run IT and Shared services for P&G in all corners of the world.

              “I think that bad master data is a root cause for most data reliability issues but most people never really get organised enough to do something about it.”

              For example, whilst I was the CIO of P&G India in 1995-8, we realised that our third-party distributors all had different standards for things like customer, order number, financial payments etc However, getting all this data harmonized was key to getting transparency into our retail operations. Trying to align all of those was my first insight into the incredible importance of master data.

              You are a proponent of outcomes-based processes – what part can or could data management play in their definition and execution?

              I honestly think that the future of business operations – internal and external – is  outcome-based processes. Let me illustrate with a common example.  Most companies run travel and expenses as a combination of 4 or 5 different processes but by contrast many tech-savvy start-ups manage travel very differently. They have an online system that spits out a budget number for the trip and that’s it – the process is done. You can book your tickets where you want, you use the company credit card and then there is no need to do any further expense reporting. I offer this as an example, because while the outcome of employee travel at reasonable cost is all that matters, in many companies sub-processes like travel and expense management have acquired a life of their own.

              “The required outcome of a business trip is to get to the specific meeting and everything else is a waste in terms of processes. You can facilitate the focus on the outcome by focusing at the business outcome related master data fields – the actual physical meeting or conversation related elements or the cost elements.”

              Everything else is a transactional, in-process data item.

              What is the role of data governance in these processes?

              Strong data governance is the foundation for effective master data. P&G has been at the forefront of driving master data management standards for the industry via the global master data consortium and through that work we have learned many lessons.

              “Eventually we all come to the realisation that organisational entities like a company are just a silo of a transaction that passes through different companies – our suppliers, our customers and ourselves. For transactions to cross this virtual company you have to be able to speak the same language.”

              Thanks to the effort of that group there are now standards across master data fields in most of the manufacturing related items. Driving those standards and governing them for the industry and the company are some of the most important roles that an IT professional can play.

              “I read a statistic that in the order-management process, issues related to master data account for about two thirds of all the losses that happen. That’s an astounding number. That’s one of the reasons why master data, although relatively unknown to many senior business leaders, is so important.”

              How would you define “modern” data management and how important is it to the success of digital transformation?

              “I distinguish the modern data masters from the traditional ones by the sheer ambition of the modern ones to control not just 60-80% of master data but 100%.”

              To explain further – the traditional strategies of data management were to drive single standards for a given field, e.g. a consistent employee or product number across the enterprise and outside.. That sounds like a worthy cause, but in reality most companies could never get past 60-80% accuracy. The gap was caused by two things. The first was human error to some extent.

              “The other root cause was the lack of understanding that master data is dynamic, not static.”

              For example, if you take the same bottle of shampoo, the weight could vary greatly based on different stages of product research, product development and manufacturing. It would also vary by country based on rules of filling the bottle. There is no static truth, there is only dynamic truth.

              “Modern data masters use different approaches and technologies including graph databases; a dynamic understanding of how data changes with time and tools and techniques including AI to manage that. I think that is really important in today’s world if you want to drive digital transformation of the enterprise.”

              How exactly is that important to the success of digital transformation?

              I’ve already mentioned that traditional master data models can only solve for 60-80% of all of the potential master data issues and that two thirds of the issues in order management relate to master data. This means you are limited as to how much the enterprise process can be digitised with traditional methods.

              To do a much better job of replicating your business model into a digital framework then you have to look for the next generation of capabilities. These could include AI and newer technologies – potentially Blockchain – and several other elements.  Then you must build on that type of foundation to digitise the whole enterprise.

              These are very different sets of technologies than what was available to the previous generation of people like me when we did automation about 30 years ago. You were limited in scope and size and how much you could imagine the world in a digital lens. That has evolved and changed, and thank goodness for that! Newer technologies, newer paradigms of looking at outcomes and newer approaches to digitising the world have assumed so much importance.

              What are your top 3 tips or resources to share for aspiring modern data masters?

              The three things I would share with modern data masters are:

              1. In order to survive the fourth industrial revolution we are going to have to reimagine and change the way we do business. That extends to master data as well.

              “Don’t be happy with the 10% improvement year to year, ask yourself how to get the 10x improvement . That level of improvement in master data is necessary in the current digital disruption.”

              1. Have people look at work processes end-to-end. Look at master data in terms of the entire virtual company – the total supply chain including your clients and suppliers – and create an ecosystem to drive standards across that
              2. Discipline – I based my book on the same checklist methodology that was used in the airline and medical industries to eliminate defects in day to day operations. That’s what I apply to digital transformation and in my 30+ years of experience I have continued to apply to master data. It is an area that can be broken down into a checklist where you can measure and improve – that would be my suggestion.

              You have a lot of experience and success in the shared services field – can you tell us about a project where things did not go so well; what you did to fix this and what you learned from that?

              Absolutely yes! Several years ago at P&G we were working on standardising and streamlining trade funds management for the company. In CPG and retail there is a lot of money allocated to promotions like BOGOF and discounting. It is very hard to get accountability and accuracy of those transactions and therefore measure which funds are productively spent.

              At P&G we tried to use a standard system across the world, thinking that if we standardised we could improve efficiency, but that was almost impossible. In different countries and their unique trade practices, the way you define a return on a promotion varies dramatically.

              “We assumed we could standardise the way local business practices were run across the world. In many ways this was a master data mistake.”

              We very quickly pivoted and went for a two-tier architecture. We could standardise many data items – for example the management of accounting within P&G across the world – but we created separate localised systems across the world for dealing with clients and local country regulations with different master data.

              What trends or changes do you predict to the data management arena in the next few years?

              1. The growing realisation of the importance of master data beyond IT professionals. Digital transformation has become a more accepted topic and now most business leaders are acknowledging the need for a standard set of definitions.
              2. “The second thing I predict is the evolution of master data technologies from static to dynamic. Traditional master data management tools and technologies suffered because they were designed for static data – offerings like Reltio are very interesting here because they try to mimic the real world.”
              3. The investment in master data within ecosystems is going to increase dramatically. People are going to realise that most of the waste that happens is at the seams of large organisations – not having a common language between the accounts payable of one company and the accounts receivable of another company means both companies are wasting resources and money. There will be a lot of attention and investment on these things.

              What do you like to do outside of work?

              I like to stay busy! Everything from handy man remodelling jobs at home to creative stuff like painting and other things.  I also like history – we travel a lot as a family so I do a lot of reading and research and I absolutely love historical fiction because I think history does repeat itself.

              Then there’s my new book, called “Why digital transformations fail”.

              “The surprising reasons that most fail is firstly because most leaders don’t define digital transformation correctly – they think about it as a use for technology or as an incremental change and not a complete reimagination of how business is done. Secondly they fail because of a lack of discipline in how change is executed.”

              “I guess the common theme across all of this is that I absolutely need to stay occupied or otherwise I get destructive and you don’t want that to happen!”

              Which is your favourite fiction book, programme or film and why?

              I have several really favourite authors, but Bernard Cornwell is one of my favourites and the other one is Conn Iggulden – they are both very good at mixing history with fiction. They have the ability to bring an old era to life and yet make it feel like it is contemporary because of the way people act and behave.

              In keeping with the historical theme my favourite movie is “Life is Beautiful” the story of a Jewish Italian man during the second world war. Anything that goes back to that era really is fascinating to me.

              “I don’t know if it is just a cultural thing but we also like to do everything together as a family. My daughters at age 26 to 25 joke that everything from buying a new car to a dinner set is a family decision but hey – y’know – it’s fun to do that!”

              #ModernDataMasters: Owen Lewis, CEO, Agile Solutions

              Kate Tickner, Reltio

                Owen Lewis is the CEO of Agile Solutions UK a specialist data management consultancy that focuses on tangible business benefits. He co-founded Agile Solutions in 2014 to help clients obtain value from data by better combining business, data and technology strategy.

                How did you get into data management and what drove you to set up a data management company?

                My starting point was actually in print – believe it or not I was one of the last print finishing apprentices in the UK. After that I took a degree in Computer Science. In the early days I worked in data transformation for data into banks through digital printing – amazing that I trained to do all these elaborate hand-crafted books and ended up doing cheque books! But it did give me the advantage of seeing how the data was being fed into the machines for personalisation and the use of algorithms for security even back then.

                 “At the centre of everything I’ve done has always been data rather than pure technology because that is where the real value is.”

                Eventually, as an entrepreneur you hit on something that becomes stronger and stronger and that is what has happened with Agile. It helps that the market has also come towards us and data is at the heart of everything now.

                Proper business entrepreneurialism will always create jobs but it’s the quality of the careers that those jobs create which is important. Only certain businesses offer great careers and data is certainly one of those at the current time. These careers are real and they have value and that is a really good feeling – to know that you are doing that for people.

                How would you define “modern” data management and what does it /should it mean for organisations that adopt it?

                There is a maturity level to data management. If you ask people about data management and all they talk about is governance then you know they are only being driven by regulation or a concern. On the other side of things in the start up world and data driven companies, they can be purely about data and development and that is innovative as companies like FaceBook have found, often the data governance is lacking.

                “A truly mature company embraces governance and innovation and they are designed in together, not bolted on and only way you can do that is via data strategy. That has to sit directly beneath the business strategy and before technical strategy.”

                The only way that innovation and governance will be aligned properly is if you strategise in that order – business, data, technical. Modern data management is about having those things in alignment so that your business will be data-driven and governance will not be an after-thought.

                What aspects of modern data management solutions does Agile Solutions focus on?

                The cloud technologies AWS, Azure and GCP are a group representing a massive percentage of the IT market at the moment. In the same way, in the ‘90s or 2000s, most of IT would be touching SQL or one of the other databases. The current language of IT and development is really underpinned by cloud offerings. The technologies that are aligned to those offerings and make them more efficient are the ones that people are going to adopt.

                At Agile, all of our own business systems are cloud-based:

                “The cloud platform approach that we are taking as a business is critical to our own strategy but it means that we are acquiring the tools and skills that will make the journey easier for us and our clients.”

                What are your top 3 tips or resources to share for aspiring modern data masters?

                If you really want to create an opportunity for yourself you have to understand the business value of data because it underpins everything.

                You’ll also need to know why things are designed the way they are and why they have to operate the way they do which means you’ll have to understand the underlying capabilities of technology too.

                “New technologies can do a lot more than the old ones could. Previously everything in the IT world was designed around whether SQL could deliver it, whereas there are now many more options for us. Graph databases and their adoption have proved that and there is lots more to come. That’s got to be a good thing.”

                You need to know whether you want to be on the business or IT side primarily but be able to talk to both because business and IT don’t necessarily get on well together. If you want to be an inventor you probably need to focus more on the business side but if you want to make your way successfully through a large organisation or work in consulting then you need to be more on the technical side because those are the skills that are in demand.

                Finally, my personal tip, never be in awe of current methodologies and processes.

                “There’s always a better way, if you look at it and have the understanding to prove it. If you know what you are doing and why you are doing it then you then have the tools in front of you to do it better.”

                There is a large portion of the community, especially in IT, who keep on doing things the way they have always done and never believe that anything can be done in a different way – a better way. You just have to keep your eyes open for that.

                How important is experience versus willingness-to-innovate for a modern data master?

                Experience is always going to be required. You can’t trade that out and replace it with anything else. The trouble is that often with experience comes the inclination to do things the same way you have always done.

                “For super-success you have to keep learning or you will get left behind – never kid yourself that you learn one thing and stay with it – it’s a continuous learning process and you never stop.”

                What trends or changes do you predict to the data management arena in the next few years?

                The big data era is maturing and the technologies that first appeared with big data will be enveloped into the cloud technologies. I predicted about three years ago that the age of big data would be quite short and that it would be very quickly overtaken by the age of big data governance.

                What I mean by this is that politically and economically people are seeing the effects that big data technologies are going to have – especially when it is linked visually or actively to them every day by some kind of AI interaction. This will drive the establishment to recognise that some kind of protection needs to be put in place.

                “The key thing there is that if you are going to protect anything then you need to govern your data properly – AI is only as only as smart or restricted or governed as the data it is given to work with. The data has to be trustworthy and the minute regulation is involved, of good quality, otherwise there will be consequences and fines.”

                How well placed is Agile Solutions to continue to grow based on these trends/changes?

                We have the people and we are developing them. We will continue to hire people that have experience in the data-space but we are also building an academy for our graduate hires. That mixture of the experience and the new people and new technologies will really help us.

                We are very well positioned in terms of industry experience and we are able to apply governance principals as well as talking about innovation. In the future the innovation discussions will turn much more to governance and the new people who are innovating won’t have the experience or knowledge of governance. In the same way if you just show up talking about governance you can stifle innovation. I think we are able to talk about and advise on both.

                “I think we are in a golden age of data which is going to last at least another ten years. Data envelops everything in this world and we are always going to be busy in our line of business. That’s great for us and great for software entrepreneurialism as well.”

                What do you like to do outside of work?

                I try and see family and keep fit where I can but I don’t get a lot of time. I am hoping over the next few years to develop a few proper hobbies but business takes up a lot of time – probably more than it should. I haven’t got a lot to complain about though because things have been going relatively well.

                I did buy a hill-climb racing car a while ago but I’ve not had time to race it and unfortunately I’m not sure my eyesight or reactions are as good as when I bought it. By the time I get time to drive it I might have to find another hobby!

                Which is your favourite (science) fiction book, programme or film and why?

                I’ve always read a lot on a wide range of topics – I think that’s the hungry-mind thing. I’ve always got a pile of books by my bedside that I wade through, but I keep buying more.

                I like to learn from what’s gone before so I read a variety of different history books and enjoy that. I love sci-fi as a genre because you can pretty much invent anything.

                So what brings out your inner kidult?

                “Well the only thing I’m going to say is really funny is Rick and Morty – it’s a cartoon and it is hilarious. I’m not going into the detail because it is way too nerdy but it’s really funny and a bit edgy – just imagine a drunken Dr Who!”

                #ModernDataMasters: Scott Taylor, “The Data Whisperer”

                Kate Tickner, Reltio

                  Scott Taylor also known as “The Data Whisperer” is a firm believer in “making your data do the work,” and has enlightened many business executives to the value of proper data management by focusing on the strategic rationale and business alignment rather than technical implementation and system integration.

                  What is your background and what was your route into data management?

                  I got my start in data by working for a number of data companies such as Dun & Bradstreet and Nielsen. I think my parents would say I was hardwired for working in the master data space because instead of building with my Lego blocks I sorted them. In MDM there’s a lot of data sorting, taxonomies, ontologies etc. If your kids are sorting blocks, they might be in the master data business so watch out!

                  The companies I worked for all had taxonomy and content assets, so to deal with that I had to talk to business leaders across all sorts of global enterprises. I needed to help them understand the value of master data more from a strategic initiative perspective than one of technical implementation. I am not a practitioner in the MDM technology space – I am someone who can convey its value to the business.

                  “I’m more of a “why” guy than a “how” guy. It’s the people who have no idea what master data is and no time to learn it – but who have all the money – who really need to understand the value of it and what it can do for the enterprise.”  

                  How would you define “modern” data management and what does it /should it mean for organisations that adopt it?

                  As far as the technology goes – cloud, big data, machine learning etc – if we’re talking about that and someone hasn’t bought into the fact that they need master data at all, then none of it matters.

                  The current approach to MDM at a very high level is pretty much the same as it has always been. What’s changed is the urgency and the stakes around it.

                  “MDM and master data used to be a very clerical back office, logistical, tactical sounding discussion all about cleaning data – no CEO wants to have a conversation about data hygiene. Data janitorial work doesn’t sound very strategic however important it is.”

                  What’s happening now is the convergence of all these mega-trends – AI, Cloud, Social, Mobile, Blockchain – I can count handfuls of trends out there that are regarded as the “sexy” stuff. I look at all of those and behind each one I say: “OK it’s not going to work without master data”. Period. For example you’re not going to get IoT to work across organisations and devices without having a common data structure.

                  It always comes back to this foundational, structural data and the challenge is, it’s not very sexy. People forget than when you build big, ambitious things – ships, buildings or bridges for example – you need the nuts and bolts and you cannot build without them. Master data is the nuts and bolts, no one talks about them but you can’t do anything significant without them.

                  What are your top 3 tips or resources to share for aspiring modern data masters?

                  Well first of all they should look at the business process and see how they can improve it – without jumping to the technology – because they don’t know what they are solving for yet.

                  Backing up a bit it’s to get an understanding across the enterprise of what data is there and what needs to be mastered. It’s usually the same stuff – customer, product, vendor, asset, partner – and look for the ways that that is going to map directly to the strategic direction of their enterprise. If you look in a Chairman’s Report for any large enterprise’s 5-6 strategic priorities you’ll see that at least half of them won’t work without master data. Find those and try to link them together because for me master data is the ultimate enabler.

                  Look at the things that the CEO and CIO are really putting their weight behind – they won’t be saying they need more MDM. They could be saying they need “Customer 360” in their annual report and not even realise they need a master data strategy to do that.”

                  For example, they might say they want to be the “premier partner of choice” for their customers and yet not have a common definition of customer that everyone in their organisation understands.

                  People talk about ROI – it’s very difficult to find the ROI of cleaning a record – it’s very tactical. But what does it enable? That’s the exciting thing for me in the space – people are investing in lots of programmes that require MDM to run but they probably don’t realise it yet.

                  “Things like CRM won’t work without MDM – it makes the other stuff work better. That’s your ticket to the party.”

                  How important is experience versus willingness-to-innovate for a modern data master?

                  Experience is always important. There are a lot of great practitioners out there who know how to get it done so you’ve got to lean on that. It’s also critical that they’ve got a spark of innovation because they’ll then have to think about what to do next.

                  Many of the people with experience tend to have a lot of frustration because their dreams of master data have not come to fruition. They have spent years in their organisations and they “get it”. They totally “get it” but they can’t take that message upwards.

                  “When they bump into the CEO in the elevator they say: “We need a golden record” and the CEO says “Well that sounds expensive”. That conversation doesn’t go very well so consider telling a story about how the organization still doesn’t have a common definition of customer and can’t integrate all the disparate but valuable data across functional silos.” 

                  Data management has traditionally been positioned as a technical process. How important do you think data management knowledge is for business people – marketing professionals in particular?

                  Marketing people, more and more, need to understand the technical underpinning of master data. When they are talking about things like a CDP, if they think that is going to solve all of their customer issues, they have to realise there was already something called MDM that was already there to do at least the foundational piece.

                  Global brands are increasingly going to need to be able to master that brand entity consistently across different global markets. As people look to defend their brand and support its values they will have to understand its presence in all of these geographies and that gets really complicated, really quickly.

                  Brands could be in 100+ countries and have different product names in each of those countries but they all roll up to the same idea.

                  “The notion of protecting and managing brand is something that has to be mastered in order to work at scale. To do that across all the different channels you have to establish a common definition of brand, push it out and make it something that is standardised across your whole value chain.”

                  Agencies need to understand that, ingest it and work off those brand definitions – the media side needs to do it as well.

                  Brand messaging is funding pretty much everything we’ve got out there. All these start-ups that want to create a new app think to themselves “we’ll get an audience and then expose it to all this brand messaging” – it’s a form of advertising or marketing no matter what.

                  –           Is there a skills gap currently amongst marketers?

                  Well yes, absolutely there’s a skills gap. I love marketing, it’s telling a story and putting it into play. However, the more marketers can understand the details and the logistical part of how these stories scale, the better. As much as the technical side needs to understand the business drivers, the business needs to understand the technical side as well. 

                  –           How can it be addressed?

                  Practical suggestions? Watch my videos! What is Master data? What’s the value of master data? Don’t get so caught up with the sexy stuff – marketers by their nature try to make everything exciting. Think of a Venn diagram with sizzle on one side and steak on the other – marketers need to be in the middle.

                  “Marketers are really good at the sizzle and sounding cool, but you’ve got to have the steak, and for me the steak means being technically accurate. I look for the sweet spot in the middle.”

                  What trends or changes do you predict to the data management arena in the next few years?

                  Rather than what I predict, let me tell you what I hope for. The first one is about data being the new oil. It’s not the new oil – everyone just grabbed onto the poetry and then tried to explain why data was or was not the new oil. If people are using a metaphor that they then have to explain, then it is not a good metaphor.

                  “Data is not the new oil, it’s not the new gold, it’s not the new electricity; it’s not the new bacon; it’s not the new tofu; it’s not the new anything. Data is data and it has always been there and the people who have managed it really well already know that. It’s a fuel sure, but in terms of the oil analogy, I hope it just goes away.”

                  There’s all this talk about big data. I could run a debate whether big data exists or not? Every time I hear people talk about it and what they’ve done with it I am wondering how that is different from just having lots and lots of data? What was “big” about that?

                  “I hope people start getting back to just regular data because that is where the real value is. It’s not as cool sounding but that is where the reality is.”

                  Which is your favourite science fiction book, programme or film and why?

                  Science fiction? OK, can I say Toy Story?

                  Well any fiction then..

                  2001 is way up there in terms of that journey – anyone who tells a great story – that’s what I love. So The Godfather. Toy Story. La La Land was a great one. When I see people do really innovative story telling I love it. No matter what – you must have a story – it has to somehow capture you and move you along.

                  “I had the chance to ask Francis Ford Coppola a question at a conference once. I asked him how he could tell what was a good story and he said “You just know, you read it and it just works. It captures your imagination and takes you somewhere different”. Being a marketer or a seller, you have to be able to tell a good story, so anyone tells a good story I’m all for that.”

                  What do you like to do to relax outside of work?

                  I live in an awesome place – Black Rock, Connecticut. We have an apartment in a building that overhangs the water, that they would never allow to be built today because it is a monstrosity. But we don’t care because we’re inside of it and we look out at an idyllic New England harbour town with a lighthouse. One thing I do to relax is that any time it’s calm, I kayak.

                  “I’ve learned about life from kayaking because if you want to kayak when it’s nice out then you have to go and kayak when it’s nice out. You have to go and do it. You can’t delay and wait too long because the conditions will have changed.”

                  Also I’ve learned philosophically that you can’t control everything. If you are out there you have to pay attention and if there’s a dark cloud you can’t think your way around it. You just have to go to shore. I take things like that to heart every day.

                  “I also do a lot of juggling – I can juggle pins. I can blow square and really really large Bubbles. Perhaps I could do that later? I don’t have the right tools here, but we can try that next time!