How CDOs & CIOs are Driving Digital Transformation
Ajay Khanna, VP of Marketing, Reltio
I recently got an opportunity to present at MITCDOIQ Symposium in Cambridge, MA. Here is the outline of my presentation where I discussed how today’s CIOs and CDOs are driving digital transformation across their enterprises. It discusses the key drivers for digital transformation and how Modern Data Management is helping them with their initiatives. You can now download my slides from the event from this page.
Today’s business landscape more dynamic than ever. New revenue models, stringent regulations and high customer expectations are forcing organizations to evolve or face being overrun by more nimble competitors.
CDOs and CIOs of established business are looking to digital transformation as a key initiative. But what exactly does digital transformation entail? At its core, any digital transformation requires clean and consistent data, reconciled across systems and channels. An enterprise-wide data management foundation that ensures real-time access to reliable data of all types at scale and is non-negotiable. Data access must be democratized across all groups and divisions so that teams can get a 360-degree view of customers, products, organizations and more.
However, it’s not just about disconnected siloed analytics. It’s about the next generation of operational data-driven applications that allow frontline business users to gain relevant insight and intelligent recommended actions so they can achieve their goals. This session explores how some of the largest companies in the world are transforming themselves using the same modern data management technology used by Internet giants such as Amazon, Facebook, LinkedIn and Google.
The presentation covers the following topics:
Changes in business environment and need for agility
Digital transformation drivers
Digital transformation examples
Data-driven digital transformation with Modern Data Management
Please fill out the form below to download the presentation slides:
“CIOs are now spending double their time on business priorities, strategy and architecture (from 8.1% in 2014 to 16.2% in 2015). This is where CIOs spend most of their time, followed by forming IT strategy (11.9%) and IT operations (8.0%). Further, the most common measures of CIO performance are IT’s contribution to business strategy (35.5%); availability/up-time (34%); IT user/ customer satisfaction (31.9%), satisfaction of the customers of the business (30.3%); and value of IT to the business (29.6%)”
— SIM 2106 IT Trends Survey of 1,218 members, from 785 organizations, with total revenues of nearly $5 trillion and $250 billion in 2015 IT spending
#1. Alignment of IT with the Business
It’s no surprise this issue is #1, alignment between IT and business is a recurring challenge. Why? Because IT has to grapple with backend tools and infrastructure, while business cares about rapid access to the data to make informed decisions. Business often views IT investments in big data Hadoop as “franken-projects” that don’t correlate to the problems that need to be addressed today.
A platform that combines a modern data management Platform as a Service (PaaS) that seamlessly delivers frontline business facing applications can help. This ensures that the technology is enabling fast time to value with both teams “pulling on the same rope” to achieve company goals.
#2. Security and Privacy
Security and privacy continues to be front and center. With an increasingly digital economy, the age of social media, and stringent data management regulations, which are different based on industry and geography.
A modern data management PaaS will provide the highest level of compliance and data governance. Enabling IT to maintain access to data by role and business goals, down to the attribute-level. A detailed audit log tracks not only modifications and access to data, but even search terms and parameters. For CIOs who are concerned about public cloud providers, such as Amazon Web Services, who host modern PaaS technology, are proven and relied upon by the CIA.
#3. Speed of IT Delivery and Time to Market
The billions of dollars spent by LOB teams on self-service data preparation, self-service business intelligence, and outsourced “as-a-service insights and intelligence” reflect a desire to shortcut IT projects are typically measured in months and years, not days and weeks.
A 100% cloud PaaS ensuring agility through IaaS (Infrastructure as a Service) partners, such as Amazon Web Services has built-in Daas (Data as a Service) to rapidly onboard and blend data across all sources. Ultimately resulting in SaaS data-driven applications that deliver information into the hands of users at the speed of business, optimizing time to value.
#4. Innovation
No CIO has ever said “no thanks” to innovation. The problem lies in the legacy infrastructure which acts as a resource and budget anchor, preventing innovation. Even when budget is available, the onslaught of new technologies (witness the never ending spawning of Apache open source projects) makes new initiatives obsolete even before POCs have been completed.
Modern PaaS incorporates the latest NoSQL, big data, analytics and machine learning technologies such as Apache Cassandra, Spark and ElasticSearch. A metadata foundation supports the logical definition of the business, unconstrained by physical storage and implementation. In effect, a modern PaaS acts as a technology portfolio manager, swapping out the latest in innovative technologies when they mature. Ensuring that CIOs never have to fund those random Hadoop research projects again.
#5. Business Productivity & Efficiency
How can IT support business productivity and efficiency when many IT teams don’t fully understand the use of data once it reaches the hands of the frontline business user? IT’s focus has long been to ensure the security, management, and governance of the data. Data quality and reliability is a fundamental need that impacts business and an area in which IT and business must collaborate because only business truly understands the data, and whether it is comprehensive, and of high enough quality to improve operational execution and decision making.
A modern PaaS is rooted on a foundation of master data management (MDM) process and discipline. The best PaaS technology providers are also ranked as leaders in the Forrester Wave for MDM delivering not only in current offering and vision, but in delivering the highest business value and context.
#6. IT Value Proposition to the Business
Those not in the CIO shoes might think that this is the same as “#1 Alignment of IT to the business”. But this important topic of concern is around not just the types of projects that IT executes on, but ultimately the ROI delivered, as measured by business outcomes. CIOs are in between a rock and a hard place because today’s tools and platforms start and end with IT specific measures as regards to ROI (e.g. reduction in skilled IT experts, faster data loads, better performance). There has not been a way to accurately correlate IT investment to business outcomes … until now.
Combining both an IT data management PaaS – that is able to track the sourcing, lineage and consumption history of every attribute of every record – with the seamless integration and delivery of data-driven applications – in which business users leverage the same data to make business decisions and take action – is the ultimate solution. It gives IT teams full visibility and metrication of business outcomes. For the first time, IT and business can close the loop on ROI, directly recognizing the value IT brings to the table.
#7. IT Agility & Flexibility
Cloud embodies how CIOs can be more agile and flexible. Eliminating heavyweight, expensive to install and maintain on-premises hardware and software is critical. As processing power and the cost of storage keeps falling, companies who are handcuffed to massive CAPEX investments are unable to pivot when business needs inevitably change. The use of legacy on-premises software, upon which 12 to 18 month upgrade versions to receive new functionality also prevents any timely innovative competitive advantage.
They key is not just 100% cloud, but multi-tenant cloud. Like Salesforce.com and other innovative public cloud providers, multi-tenant Cloud delivers no impact upgrades 3 times a year. This not only provides the latest technology and features (see #4. Innovation) as soon as it becomes mature and viable, but dramatically eliminates the hidden costs of upgrade of on-premises or managed services/hosted solutions masquerading as cloud offerings. Even with unlimited financial flexibility for upgrades, the pain of on-premises hardware and software upgrade cycles comes from missed opportunities when resources are tied up simply moving from one version to another in an endless cycle.
#8. IT Cost Reduction & Controls
Cloud again helps here, this time in the form of OPEX. The ability to dial-up and more importantly dial-down storage, processing and other costs, ensures that IT can spend what it needs to and not a penny more. Shedding “over procuremen-titus” is great, but savings can also come from consolidation of IT investments in large enterprises, across divisions. This however requires significant coordination and collaboration between teams, and the elimination of “Shadow IT“.
Meanwhile the dramatic reduction in the cost of devices is now juxtaposed with the consumerization of IT, with business users demanding BYOD (Bring your own device) options. This is a security risk as well as a costly endeavor to ensure that applications run consistently on different variations of devices (mobile and PC), and versions of operating systems.
Using built-in Data as a Service can dramatically lower the cost of data acquisition from third party vendors. It can be used as a “clearing-house” to manage and monitor the consumption of data across groups, eliminating redundant data purchases. Data-driven applications can be delivered via industry standard HTML5 form, enabling embedding in existing interfaces and full compatibility with all browsers, again dramatically reducing development and support costs.
#9. Business Agility & Flexibility
The best way for IT to support business agility and flexibility is to bring together reliable data, relevant insights, and to have data-driven applications increase the speed and accuracy of actions taken by frontline business users, as business conditions fluctuate. Unfortunately today’s applications are siloed and process-driven. Focusing on a single group (e.g. CRM for sales, Marketing Automation for marketing), and there is little collaboration across teams. An isolated problem solving focus results in siloed data, which in turn necessitates yet more technology to blend and manage data to form an elusive customer or product 360-degree view.
Eliminating data silos should be a mission for all CIOs. By bringing together data across the enterprise, with MDM rigor for reliable data quality, personalized contextual relevant insights, and machine learning formulated recommended actions can help business teams be more agile. A single pool of information managed at big data scale, from a modern PaaS uncovers hidden business relationships using graph technology(similar to those used by LinkedIn, Facebook and Google), to reveal insights for competitive advantage. By going beyond just master data, and including transactions and interactions, a modern PaaS forms the foundation for analytics and machine learning. A new breed of PaaS allows IT teams to respond to business needs for process changes, or new sources of data in a timeframe previously deemed impossible.
#10. Business Cost Reduction & Controls
Many IT departments require business approval for funding of projects, so a focus on their own IT costs are mutually beneficial. However business teams also spend billions every year in their search for agility on disparate tools for business intelligence and self-service data prep. IT needs to deliver a reliable data foundation upon which business teams can gain the trusted and relevant insight they need, without searching for a needle in a haystack through ad-hoc queries. Another area that IT can help is the significant cost of training of users on how to use new applications and tools.
A modern data management PaaS that seamlessly delivers data-driven apps can reduce or eliminate business’ reliance or appetite for standalone self-service tools. By delivering the right information into the hands of the right users at the right time these next generation role and context sensitive apps are based on the exact same easy-to-use, zero training needs as popular apps such as Facebook, LinkedIn, Amazon and Google.
Thanks for reading this rather lengthy post. A modern PaaS is like a Swiss army knife, architected to handle any challenge past, present and future. I welcome your feedback and comments.
5 Things CIOs and CDOs Need to Know About Pokémon GO
Disclaimer: I was never part of the Pokémon craze back in the 1990s nor have I actually played Pokémon GO (the Guardian has a good Pokémon GO 101 guide here), however like many I’ve felt and seen the phenomenon both virtually in social media, and physically with people wandering around streets with their phones trying to capture them.
Because Pokémon GO involves a lot of SMAC (Social, Mobile, Analytics, Cloud), and tons of data – topics I’m constantly immersed in given my role as CPO at Reltio – I have a few observations to which may help CIOs and CDOs.
#5. Security risk via BYOD or casual access via personal devices
If you have a Bring Your Own Device (BYOD) policy, or employees occasionally accessing corporate data from their own devices, Pokémon GO increases the risk of security breach, data loss and intrusion.
One of the security or privacy holes that was uncovered involves permissions being granted to Google emails, docs and other areas by unsuspecting Pokémon players, when they used their iPhones and Google user accounts to authorize and play the game. While this issue has been addressed through an update by the game creator Niantic, to now collect only “basic” info like user ID and email address, anyone who previously downloaded the app will have to update it for it to take effect.
If you have employees who are outside the US or in geographies where Pokémon GO is not yet available, there are reports of “evil” APKs (Android Application Packages) that enable game play through “sideloading” which loads apps outside of the official app store. These apps could potentially spy on or gain access to data.
While the risks presented by Pokémon GO aren’t unusual as compared to any other popular application, its global phenomenon and ubiquity, coupled with increasing BYOD, and personal device access to corporate something that CIOs should be aware of. Not to mention theft of devices from thieves apparently laying in wait at locations.
#4. Data monetization could exceed in-app purchases in value
According to Sensor Tower, a company that tracks app usage, Pokémon GO had 10M+ downloads within the first week of launch and is now generating more revenue than any other iPhone app in the US. While Pokémon GO doesn’t charge a subscription fee, it offers in app purchases such as Poké Balls used in battle.
Oddly Nintendo, whose stock soared shortly after the release may benefit the least from these purchases. Estimates have it that out of the purchase price of 100 Pokéballs, Pokémon 30 would go to Apple, 30 to Niantic the company behind the game, 30 to Pokémon and 10 to Nintendo. Nintendo does own 32% of Pokémon company, and Google does have an investment in Niantic, having spun it out last year.
But the interesting thought which might make CDOs sit up and pay attention, is that the value in the game in the short term may come from the in-app purchases, the data being gathered (even after alleviating Google account identity concerns) may be significantly more valuable.
Geospatial data captured about a player’s location at a specific time has tremendous value for advertisers and can be analyzed to offer services. Similarly images captured from the augmented reality could be used to build up a library, similar to Google Street view, or other as yet untapped purposes. But much of this data may be unusable, unless it can be accurately correlated to other elements of a user’s 360-degree profile, and levels of privacy are respected and addressed.
Again this “latent” data captured during the course of mobile phone usage is already happening today, and Pokémon GO just serves to magnify the data collection at scale. Enterprise CDO’s tasked with thinking about how to monetize their own corporate data assets within their industry first need to ensure that their data is clean and reliable, with privacy, audit and licensing controls before attempting this at home.
#3. Gamefication drives activity with expected and unexpected results
It’s been written that Pokémon GO is the perfect storm of nostalgia (for millennials who grew up with Pokémon), competitive spirit, social interaction, and a desire in us all to just immerse ourselves in something fun. Intentionally or not, Pokémon GO has actually gotten people exercising, moving around and engaging with the outside world. Because of the varied locations, people have been walking more than they have in a long time, even jumping as directed to play the game. Others have used driving services like Uber in an attempt to move around their area in a safe manner, while the lazy (and resourceful) are using drones to do their Pokémon GO hunting. With every new craze, good and bad things can result. Gamers have reported being robbed, and even finding dead bodies when searching.
In a traditional business setting, something that can motivate, inspire and deliver excitement and gratification at a personal level would be refreshing. New data-driven applications provide the framework for social collaboration, and even gamefication (points or rewards) as individuals and teams can compete on tasks from improving data quality, to providing feedback and insight into the strength of hidden relationships between people, products, organizations and more. As CDOs look to rally everyone across the enterprise to help govern, manage, and enrich data as a valuable asset, such concepts can play a big motivational role.
#2. Cloud and elastic compute is critical to handle spikes in demand
Even with the well publicized and documented value of public cloud and cloud computing, many remain unconvinced by the inherent value of public cloud. There are business reasons why companies due to real or imagined security concerns, are not ready or willing to adopt public cloud such as AWS, but the benefits of elasticity in both compute and storage are hard to ignore.
Continuous uptime and handling scalability spikes are just a small fraction of the benefits. Those mired in on-premises software are stuck upgrading once a year or longer, while multi-tenant platform and applications continuously deliver zero impact upgrades 3 times a year or more, giving companies the highest level of competitive advantage.
#1. Simple, easy to use UX drives engagement
Pokémon GO’s success can also be attributed to a low learning curve. Like Facebook, LinkedIn and other mobile and intuitive applications, no training, or formal tutorials are required to play and participate.
Continuous feedback through alerts and notifications when characters appear or are nearby, keep the user engaged, and as a cousin of gamification, UIs that show Pokémons captured ensure gratification and encourages continued engagement.
Today’s business applications need to evolve into their data-driven consumer brethren that are mobile, easy to use, and responsive. Notably Pokémon GO launched on both, iOS and Android at the same time, this is also a prelude to the expectations of business users who expect access to their data, anytime, anywhere and from any device.
Increasingly “smart” data-driven applications that use the vast amount of data accumulated can also deliver Apple Siri or Amazon “Alexa” like recommendations, truly helping the business user beyond just capturing and returning back data as entered by users.
One parting thought around Pokémon GO is the obvious question of when augmented and virtual reality will enter the business realm. Pokémon GO overlays characters on the screen in the location and setting, which could just be a precursor to the introduction of business UI in industries where a high-degree of immersion can be beneficial.
Dynamics between the CDO & the CIO: The Case of a Major Pharmaceutical Company
Reltio is one of the sponsors at the excellent MITCDOIQ Symposium July 12-14, 2016, hosted by Richard Wang, Director, Chief Data Officer & Info Quality Program at Massachusetts Institute of Technology (MIT)
“The role of the CIO is focused on how to transform the business with new innovative business processes, to reduce cost with productive business processes and best industry practices, to increase customer satisfaction with new services and channels, to address business compliance and to develop platforms for growth and globalization. The role of the CDO is to lead the data vision, mission, and culture across the organization by delivering data capabilities that accelerate their organization’s strategy. Recognizing that leading a data function has become a specialized discipline, with skills unique from those traditionally found within IT, the CDO advances business interests through partnering with technology. This discussion covers the views of the CIO and CDO of a major pharmaceutical company on the dynamics of the two roles, spanning collaboration, competition and conflict.”
Daniel LeBeau provided details that an initial focus at GSK involved marshaling big data on behalf of the R&D division (other divisions typically within a pharma org include manufacturing and commercial).
Data and Process: Two sides of the Moon
He discussed today’s data-driven focus as still being 2 sides of a moon where “data” has always been on one side, with “process” the other. Both need similar care and attention. He stated that in this era of data, mixing of domains, and multi-domain is critical in today’s environment. It’s no longer acceptable to just have information siloed in applications.
It’s about balancing speed and quality
Throughout the discussion he also reiterated that in all activities there must be a balance between speed and quality. He cited that in managing large sets of data, there must be a discipline and focus on dealing with the data that has the highest value as there simply aren’t enough bodies or resources to clean all the data.
One such contrast made was information extracted from medical articles or journals that are of higher value and quality vs. social media data such as tweets. Along those lines he also emphasized that there needed to be equal effort in bringing data into a data lake, and the quality of that data. This statement very much rings true in many big data initiatives where companies who had plunged headlong into Hadoop projects, were now finding compliance, governance and data reliability a challenge.
Does the R&D platform provide data that can be reused by other groups?
Daniel rightly pointed out that the type, size and scope of the data for R&D is fundamentally different to that say a commercial model, where multichannel interactions and single view of HCP/HCO is the focus. He felt that the parallels to R&D might be more on the consumer marketing side of commercial in terms of targeting and data volumes and types. Regardless, leveraging existing technology and infrastructure was a goal. With prioritization and again balance and focus was key.
On how his CIO role interacts with Mark Ramsey’s CDO role
When asked about the technology and ultimately Hadoop platform used for the R&D initiative, Daniel pointed out the tremendous value that Mark brought to the table given his experience. He stated that “There wasn’t much debate as to what technology to use, given Mark’s experience. We trust his judgment.”
Mark Ramsey, opened with the notion that “available data can help make better decisions even before any R&D is ever performed.” He had an entertaining anecdote around how he sent out a survey to scientists to get their input about access to data and other challenges. In the end he got an unheard of 15% response rate, with the server hosting the survey crashing due to interest and responses. The most common refrain from respondents? “I have access to my own data, but how can I get access to data that’s external to my ownership or per view?” Many expressed frustration and fatigue trying to get to data that could help them do their jobs better.
Regarding security vs. data quality
Mark was asked how GSK balances the need for innovation vs. the perceived risk taking that typically doesn’t sit well within highly regulated industries and organizations such as life sciences. He pointed out that “my best friend is the chief information security officer (CISO)” and also noted that there is a growing sense of reality that “poor data quality is as much a risk, if not a greater risk than traditional security measures.”
On standards and data governance
He described the different industry standards that GSK adheres to when creating data, such as Clinical Data Interchange Standards Consortium (CDISC) for trial data, and EHR data which has more than one standard. The refrain of “the thing about standards is that there are more than one,” rings true.
He set the record straight that at GSK, as CDO he does not own governance. “Business owns the data and we support them by ensuring quality, accuracy and relevance, so that they can use it as a strategic asset.” He did highlight that getting business teams to correct and curate their data at source benefits everyone. This is a similar to how commercial operations and sales teams are collaborating to improve data quality.
Will GSK use data disruptively for new models, like Uber?
Mark responded to this question by pointing out that there are several areas within life sciences that could be improved. Principally “it takes 6 to 20 years to bring a drug to market.” A transformational change through data, would be to make this process more efficient. He pointed to GSK’s participation in the National Cancer Institute Moonshot project announced just a couple of weeks ago, as an example. Monetization of data, isn’t always in the form of an AirBnB or Uber application.
On staying focused and aligned
Both Mark and Daniel agreed that having a core team aligned with focus was key to making their initiatives successful. The learning is to keep the ball moving by extending beyond the core team, to ensure that new groups participating have the same alignment. They both pointed out that despite the size of GSK, they have been able to respond in an agile fashion, very much getting things done in a startup manner, getting agreement that having to be right faster necessitates a different approach.
CLOSING REMARKS
Lynda M. Applegate, who did a masterful job of moderating the discussion, closed out with a set of burning questions from the audience, one of which was from Richard Wang himself, who asked for an example of tension between Daniel and Mark (in the CIO vs. CDO) role. It’s a testament to both that the primary example that they agreed on was the age-old tension of procurement of capacity, in this case 6PB of storage. That type of requirement and fulfillment never goes away, regardless of role, and Daniel rightly pointed out that as a CIO he is focused on ensuring that excessive procurement of capacity is curbed regardless of the requester.
Finally a question around the growing trend of bringing apps to data (e.g. through data-driven applications) was adeptly handled as part of the current trend on the “data side of the moon”, with Daniel describing how reliable data brought together can form the basis for apps to be created that meet the direct contextual need of the business users.
OBSERVATIONS
This was a great session, and worth the price of admission to the conference alone. Credit Richard Wang for bringing Daniel (who is from France) and Mark together as their time is obviously precious. Some key takeaways from my perspective were the need to balance speed of execution with reliable data quality. And the agility that a large company such as GSK has been able to achieve by getting alignment, and addressing security and governance issues as they surface.
It’s been well documented that the vote doesn’t mean that the UK is leaving the EU tomorrow. Some speculate it could take until 2020 before any action is taken. But companies across the globe do need to plan for that eventuality, and one key area is ensuring that they remain agile with their data management, and privacy protection strategies.
A major analyst firm wasted no time in issuing a research note titled “CIOs Must Act to Prepare for Changes Triggered by Brexit”. The note covered a wide variety of areas from cost optimization, people and talent through to governance and operating model changes.
“Businesses in Europe will see a stall in IT spending as a result of the U.K. vote to leave the European Union. CIOs need to provide frequent, open communication and create a task force to prepare for the changes.”
In the area of data management, many have been quick to point out that the General Data Protection Regulation (GDPR) passed by the EU late 2015 already has strong requirements as it pertains to:
Accountability of businesses to demonstrate compliance including privacy impact assessments, key in healthcare data, in which the risks to an individual during the use of that data must be detailed
Data erasure aka “the right to be forgotten”, meaning removing any historical activities made by individuals captured as part of their digital activities
Profiling which relates to the need to obtain permission from individuals before any of their profile data is used to evaluate their behavior. Credit scores are an example of such profiling
Data breach notifications that dictate the minimum acceptable time periods upon which individuals or organizations must be notified when profiles containing their data is compromised
If the UK is no longer part of the EU, this may seemingly free UK companies from having to conform. However the GDPR is likely to be enacted in 2018, before the UK would leave in say 2020. And the UK and other companies doing business in the EU would still have to conform.
Additionally the GDPR actually determines data security and privacy policies for members of another group known as the European Economic Area (EEA). The analyst firm further points out
“Brexit vote applies to the U.K. leaving the EU, it does not address the question of whether the U.K. will remain within the EEA (for example, Iceland, Norway and Liechtenstein are members of the EEA, but not the EU). Consequently, CIOs with data located in the U.K. will still need to continue with plans to comply with the new regulation until more information is provided on the U.K.’s future position in the EEA.”
An Information Week article “Brexit: Will Cloud Vendors Hear London Calling?” speculates how Brexit might impact the investments being made in data centers by giants such as Amazon and Microsoft.
Amazon Web Services and Microsoft are in the process of adding to their cloud facilities in the UK. IBM has already done so. All were trying to establish cloud centers close to what has become the emerging financial center of the EU.
While an article in the Financial times takes another perspective suggesting that
“Regional Cloud service providers would not be able to reach the scale needed to compete with global rivals, instead forcing them to rely on local data centers run by Amazon Web Services and Microsoft, which already operate at an order of magnitude, this person said. “What we’re moving towards is a duopoly of AWS and Microsoft.””
As we’ve seen by global reaction, and the gyrations in the stock market, the uncertainty is overwhelming.
“Data privacy and protection laws are becoming increasingly stringent, and are slowly catching up to the wealth of data being captured and used in the digital age.”
Organizations who naturally see data as an asset for digital transformation, improved customer experience, and personalized targeting, have multiple hurdles to go through to conform to not just new regulations like GDPR, or even the EU-US privacy shield. The key for any organization wanting to do business globally is to use data management platforms and technologies that are agile enough to comply with all of these laws today, and as they evolve. Only then can they maintain their competitive advantage using data, and prevent their data turning into a compliance liability.
So maybe Brexit is just another wake up call for your company’s data management strategy.
Given the opportunity there have also been no shortage of new vendors, all offering some flavor of the latest in Apache Open Source projects (Hadoop, Spark and more), NoSQL, deep learning, and in-memory processing. The landscape continues to expand leading to evaluation paralysis, or Franken-research IT projects that are destined for an unhappy ending. In this never-ending technology treadmill, you can hear business teams continuing to ask IT the grating, but very reasonable question, are we there yet?
RELIABILITY BEFORE INSIGHT
But there has always been a nagging problem. For years companies, and their business users have struggled with the reliability of their data, an essential foundation before any analytics and insights can be drawn. Gaining this level of data reliability used to be purely an IT discipline called master data management (MDM). But MDM itself used to cost millions in hardware, on-premises software and consulting services.
Data holds the key to streamlining processes, optimizing collaboration, improving customer satisfaction and meeting compliance reporting goals, but it also unlocks the formula for competitive advantage. Witness the rise of high paying job titles such as data scientists, and in the c-suite chief data officers (CDOs), are gaining in significance and popularity.
If anything the ‘big data-hype’ has just begun. It’s true that the term “Big Data” makes people think primarily of size (volume of the data), but it’s the variety, velocity and veracity (quality) of the data that has IT tied up in knots. Rather than focusing on the size of the data, their business users are rightly focusing on the size of the ‘big problems” that they need to solve.
But even IT and data savvy users are struggling with getting value out of Big Data projects. According to a report titled “CIO and Big Data – what your IT team wants you to know” 55% of big data projects fail because of the lack of communication between the top managers who had the overall project vision and those who were in charge of actually implementing it.
Big Data had started the descent into the “Trough of Disillusionment”. The report summarized the trend as follows:
“The hype related to big data continues to subside, as most end-user organizations have figured out that big data opportunities are just more opportunities and that big data is really just the data that an organization should care about. Perhaps the biggest exception to the subsiding hype around big data is the closely related discipline of data science, which remains heavily hyped and appears in the priority matrix with both a transformational benefit, as well as a short two to five years to mainstream adoption. Lagging behind data science, however, are several key disciplines that will be essential components to the maturity — and thus long-term value — for data science. Analytic governance, data classification, and information valuation and infonomics all fall into this category.”
— Gartner EIM Hype Cycle – July 2015
Another Gartner study on Hadoop adoption, 70% of respondents reported having only between 1 and 20 users accessing Hadoop, and 4% reported having no users at all.
MASTER DATA MANAGEMENT IN ITS LEGACY FORM FARES NO BETTER
If you glance 4 down the curve from Big Data, you’ll actually see MDM leading the way into the Trough of Disillusionment. Gartner explains this scenario as follows:
“A single version of the truth for master data domains, such as customer, product and asset, remains a central ambition for many organizations in the pursuit of strategic business goals. MDM is a strategic program that can take several years to achieve. The need for business case creation and program management, as well as the ability to deploy information governance and stewardship effectively, restricts MDM success to those organizations that master all these requirements. The technical challenge is to bring together the component technical capabilities of MDM (such as for data integration and data quality) in a fashion that supports real business requirements. The overall market penetration is still relatively low, due to the complexity of implementation and other organizational and technical barriers, though there is deeper penetration for specific domains such as customer and product data. Although MDM as a whole has yet to reach the bottom of the Trough of Disillusionment, it has moved significantly toward it this year.”
— Gartner EIM Hype Cycle – July 2015
For years business has funded standalone MDM initiatives, with very little to show for it. Clearly then, just putting MDM and Big Data together in its current form is the equivalent of combining two boat anchors together.
BEING DATA-DRIVEN FOCUSES ON THE BUSINESS PROBLEMS
Being “data-driven” is a business term that has also been hyped to the max over the last few years with many experts encouraging companies to use analytics and visualization to gain the insights they need to succeed. Data mania is reaching a fever pitch with the BI and Analytics market forecast by some to be $18B+, with the enterprise applications market at $32B+. That’s a lot of money being invested by business teams and IT, often in uncoordinated efforts. Unquestionably there are successes that can be tied to the investments, but the ROI of software has always been arbitrary. Without a closed loop to correlate back actions to the insights provided, it’s a continued guessing game at best.
The hype and noise shows no signs of abating so buyers of technology want to focus more on time-to-value and accuracy of outcomes. Business users in particular who experience the ease-of-use of products such as LinkedIn and Facebook as consumers, are asking tough questions of their IT counterparts: “Are we there yet?” questions are now morphing into “Why can’t I get it and why does it take so long?”, and “Why can’t my application deliver recommended actions to me like LinkedIn, and why does it make me search for something it already should know?” This powerful voice of the user is putting pressure on IT, already faced with shrinking budgets and legacy systems to maintain, not to mention continuing issues with data quality and security.
BIG DATA DOESN’T BREAKDOWN SILOS
Much of the problems also stem from the fact that despite the volume of data being captured, data is still siloed, and unrelated. So the elusive 360 view of a customer or product has never been further from reality. Individual departments and organizations are still left to making business decisions based solely on their own data. Self service BI is a billion dollar market, but business users looking at poor quality data, without the complete picture across the enterprise is a ticking time bomb.
We are now on the cusp of a revolution in what it really means to be data-driven, and size of data doesn’t matter, and traditional/legacy MDM isn’t helping with that veracity piece.
Today a holistic “modern” data management strategy is needed, implemented through platforms in the cloud that can easily combine and clean master data across internal and external sources, correlate those profiles with transactions, big data or small, and maintain those relationships to provide a core repository from which predictive analytics can be obtained.
The enterprises that will thrive will be those that can best use those platforms to deliver and share the right information on demand, anytime, anywhere across the enterprise.
Why Your Data is Likely Safer in the Cloud Than Your Own Data Center
The rapid adoption and move to public cloud highlighted by the near ubiquitous adoption of some of the largest SaaS applications in the world such as salesforce.com, Workday, Netsuite and others, has proven that companies across all industries believe that their data is safe in the cloud.
In fact, some of the largest financial institutions such as Capital One, one of the nation’s largest banks and offers credit cards, checking and savings accounts, auto loans, rewards, and online banking services for consumers and businesses, are using Amazon Web Services (AWS) as a central part of its technology strategy. As detailed in this case study, Capital one plans to reduce its data center footprint from eight to three by 2018.
“The financial service industry attracts some of the worst cyber criminals. We work closely with AWS to develop a security model, which we believe enables us to operate more securely in the public cloud than we can in our own data centers.”
— Rob Alexander, Capital One, Chief Information Officer
Capital One selected AWS for its security model and for the ability to provision infrastructure on the fly, the elasticity to handle purchasing demands at peak times, its high availability, and its pace of innovation.
What of the data, though? Intelligence agencies are drowning in it, collecting and analyzing an amalgamation of information from sensors, satellites, surveillance efforts, open data repositories and human intelligence, among other sources. Is that data really secure in the cloud? The CIA is convinced it is. – Article: The Details About the CIA’s Deal With Amazon.
Back in 2014, CIO Doug Wolfe provided an in depth look into the decision. Turns out that the CIA paid a premium, not just for the infrastructure-as-a-service, but for the availability of the applications. He name checked AWS’s Kinesis and Redshift applications as offering the kind of capabilities that the CIA needs, while also highlighting AWS’s Marketplace storefront.
“The ability to not only get the IT [platform & tools], but get the application [and] pay by the hour. That’s going to be incredibly useful to us.”
— Doug Wolfe, CIO for the CIA
However, many companies understandably still have doubts and fears around moving their data into public cloud. I recently authored a quick guide to cloud security which contains a comprehensive list of standards that AWS meets, and security questions that can be used as a reference for organizations to confidently evaluate their hosting options. It also describes how a comprehensive modern data management Platform as a Service (PaaS) leverages this platform, resulting in secure data-driven applications delivering insights directly to frontline business users. You can get your free copy here. Please let me know your thoughts.
“…Think about it: How people find jobs, build skills, sell, market and get work done and ultimately find success requires a connected professional world. It requires a vibrant network that brings together a professional’s information in LinkedIn’s public network with the information in Office 365 and Dynamics. This combination will make it possible for new experiences such as a LinkedIn newsfeed that serves up articles based on the project you are working on and Office suggesting an expert to connect with via LinkedIn to help with a task you’re trying to complete. As these experiences get more intelligent and delightful, the LinkedIn and Office 365 engagement will grow. And in turn, new opportunities will be created for monetization through individual and organization subscriptions and targeted advertising.”
In order to achieve this level of personalized, relevant insight, both Microsoft and LinkedIn have to continue to leverage power and technology of graph to capture, manage, and maintain data across relationships of entities at limitless scale. Another Verge article titled simply “Why is Microsoft buying LinkedIn?” emphasizes the power of graph across all entities, not just people.
At Reltio, we founded the company on this very premise. Our name reflects the relationships that when uncovered can profoundly change the way any company does business. That is why we created the Commercial Graph, and made it a core part of our modern data management Platform as a Service (PaaS).
The combination of internal, and third party industry data feeds, with the power of collaboration through frontline business users via data-driven applications, is exactly what LinkedIn has achieved.
We view this announcement as tremendously exciting, because it continues to validate our vision for the enterprise and all of the partners and customers who are able to take advantage of the same power that Microsoft has now acquired.
Earlier this week, I got an opportunity to present at DBTA (Database Trends and Applications) Data Summit in New York. This is a two-day event where various industry leaders join in to discuss the key industry trends and strategies about how to be more data-driven. The topics of discussion ranged from data warehouses, data lakes, IOT, to data science. I was asked to present in the category, “New Approaches to Data Management,” and track “Moving to a Modern Data Architecture.” I presented five key trends that are helping organizations capitalize on their data and make better-informed, data-driven decisions.
If we see the progression in data management, things have certainly become exciting since the start of this decade. In early to mid 90s, most of the focus was on processes with the rise of ERP, SCM and later CRM applications. At the beginning of the 2000s, businesses wanted more visibility into their performance and processes, and we saw the introduction of many analytics applications based on OLAP databases and star-schema. However, with the advent of mobile, social and cloud, things started to get interesting. Gartner referred to this as the “Nexus of forces,” and IDC as the “Third Platform.” Organizations began to seek ways to manage the huge volumes of data generated. New roles, like Data Scientist and Chief Data Officer (CDO) emerged. Today, companies are looking for ways to go beyond vanilla data management to become more data-driven. Below are the top five trends I presented:
1. MACHINE LEARNING: DATA RELIABILITY FOR BIG DATA
The first trend involves the use of machine learning to create a reliable data foundation. In the big data world, bringing data together from multiple internal and external sources can be a challenge. We are moving from manual or rules-based matching to matching done via machine learning. However, there is still much distrust on machine learning as a black box “Voodoo.” So the initial phase of machine learning is to provide transparency of the actual rules that drive the merge, and then leave it up to the user to evaluate the discovered rule and persist it in the system.
2. GRAPH: FINDING RELATIONSHIPS IN THE DATA
The next significant advancement is the graph, used to help us understand relationships across all real-life data entities. The graph aids to establish and navigate many-to-many relationships among people, products, places and organizations. Uncovering relationships using graph technology helps you solve your problems like householding in retail, or finding the most influential people in your key accounts.
3. COGNITIVE SYSTEMS: INTELLIGENT RECOMMENDATIONS
Trend number three involves intelligent systems that guide users and provide intelligent recommendations, based on data and user behavior. Intelligent recommendations can tell you how to improve your data quality, suggest new relationships in your network (like LinkedIn or Facebook) and offer next-best-actions–suggesting what would be the right time and channel to connect with a customer, or which promotion should be offered next.
4. COLLABORATIVE CURATION: CLEAN & CURRENT DATA
Sharing data across all systems and functional groups helps realize the full value of the data collected. Marketing, sales, services and support should all leverage the same reliable, consolidated data. They should be able to collaborate and contribute towards enriching the data. They should also be able to vote on data quality or the business impact of any data entity. New data-driven applications must support this.
5. DATA MONETIZATION & DaaS: NEW REVENUE STREAMS
The charter of a CDO does not only involve data governance, data integration and management. Increasingly, companies are asking CDOs to turn this data into new revenue streams. With cloud-based, Data as a Service, companies can easily monetize their data and become data brokers. Businesses can now collaborate with each other to create common data resources, and easily share or exchange data.
I had some interesting follow-up discussions with attendees. The idea of building a reliable data foundation, and discovering relationships across all data entities was the most brought up topic, because many companies are struggling with these issues. Attendees from more mature organizations talked about various machine learning algorithms and data monetization opportunities. Surely, these trends were on the top of the mind for many, and are bringing us towards the age of modern data management, where data is considered a strategic asset–not just an exhaust from application systems.
One Small Step for Data Management, A Giant Leap for Applications
A couple of weeks ago, Reltio was named a leader in The Forrester Wave™: Master Data Management, Q1 2016. While it wasn’t exactly a moon landing it was a privilege to be recognized by one of the industry’s leading independent research firms, and we do believe this to be an important step towards a data-driven future.
We’ve been told that it is a rare honor for a new entrant into the market to be cited as a leader in this comprehensive study among long-established master data management (MDM) industry players.
While Reltio was given the highest score in the strategy category, together with the second-highest score in the current offering category, what was even more significant was how we also received the highest score possible in relation to the business value and context criteria in Forrester’s report.
“The Forrester Wave for Master Data Management was published today. The results may surprise you.
MDM tools today don’t look like your father’s MDM. No longer an integration hub between applications and DBMSs, today’s tools are transitioning or have reinvented MDM to handle the context missing from system traditional implementations. Visualizations, graph repositories, big data and cloud scale, along with application like interfaces for nontechnical users, mean MDM and master data gets personal with stakeholders.”
— Michele Goetz, Principal Analyst, Forrester Research
This report is a nice milestone for Reltio as it validates our core belief that reliable data has to be the foundation of any data management strategy. We’ve been saying that like oxygen and water, reliable data is now table stakes for businesses of any size. The ability to deliver both analytical insights and operational execution in a single application for their business teams is what every company has been searching for, and it is now a reality.
“Our core mission goes beyond MDM. We are focused on simplifying all aspects of data management for IT, while delivering high value data-driven applications into the hands of frontline business users. Reltio Cloud achieves this by combining MDM with multichannel interaction data, predictive analytics, machine learning, all within a unified modern data management platform that operates at Internet scale leveraging big data.”
— Manish Sood, CEO, Reltio
For the last 12 months, we’ve been myopic in our focus on delivering fast time to value through data-driven applications that are both operational and analytical in nature. The feedback has been amazing, with both customers and partners telling us that our applications are as easy to use as Google, LinkedIn and Facebook. With unique out-of-the-box features that support suggestions and collaboration similar to major consumer sites like Amazon and Yelp, they feel they finally have the support they were missing to be more productive and competitive in their jobs. When companies select Reltio, they are getting much more than just MDM.
Our PaaS is designed to both simplify data management and integration for IT, while delivering relevant insight and recommended actions, in context to business teams. In effect, bridging the gap that has long existed between the billions being spent on IT infrastructure and tools, and the billions being spent on applications and BI by business. For emphasis, we also announced the availability of Reltio Insights, our connector and on demand Apache Spark offering, in conjunction with Databricks, on the same day the report was released.
This report is a small step in our journey and would not be possible if not for the dedication of our employees, and the support of our customers and partners. On behalf of the team at Reltio, I would like to thank everyone who shares our vision of the next wave of enterprise data-driven applications. Today it just so happens that we also solved the reliable data MDM problem, but we feel we’ve taken a big leap towards the apps of the future, and the best is yet to come.
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