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An Industry Shift for Master Data Management at Summit NYC

If you missed it, the premier industry event for master data management (MDM) in NYC took place this week, with attendees from all over the globe. The event was well attended but for many attendees, the information they were seeing was anything but business as usual.

In among the traditional sessions on master data management fundamentals, case studies and master reference data, there was a decidedly different tone to the event. 

Interest was high on graph databases, end-business user trust and access to the information through data-driven applications, and how modern data management platforms were now providing master data management as a core foundation, upon which big data, transactions, analytics and machine learning are fully integrated.

Here are some highlights:

The “Godfather of MDM” Aaron Zornes kicked things off, describing the new strategies and elements at this year’s summit. He highlighted graph databases, temporal and big data particularly as trends.



Neil Cowburn and Robert Quinn of iMiDiA delivered a lunchtime keynote describing how a modern data management platform was used for multi-billion dollar mergers and acquisitions (M&A)

He described how IT teams can now cope with data across hundreds of sources (e.g. over 96 SAP instances!) and increasing volume, variety and velocity, while managing veracity. Modern Data Management techniques were applied in an M&A use case where data collection, tracking of changes & control access were accelerated at minimal cost. And how all capabilities used for pre-merger analysis were available for post-merger competitive advantage. Attendees learned how to:

  • Leverage & enhance Master Data scope – entity overlap & cross-entity relationships
  • Support enrichment to enable the combined business teams to get more value out of the master data
  • Syndicate master data to existing operational applications & analytic platforms – all while supporting a single point of governance
  • Follow a methodology to work with the people and processes needed to co-exist with existing legacy MDM tools, while making the move to a modern data management platform

Vivian Wu of AbbVie presented as part of the Reltio sponsored virtual pharma track. She described how the limitations of a legacy and traditional MDM tool led them to select a modern data management platform. 

AbbVie used an incremental approach to deliver relevant insights while creating reliable data that could be shared company wide. Their modern data management included master data, transaction, social and third-party data delivered through mobile and desktop data-driven business applications that improve the productivity of their frontline business users every day.

Attendees learned how:

  • A cloud-based modern data management platform was selected & how it co-exists with existing systems/applications
  • Data quality can be continuously approved, while seamlessly segmenting & analyzing information
  • To plan to start small & expand to limitless possibilities company-wide 

In a particularly poignant slide she described how companies should insist that their third party data providers provide on demand subscription-based data-as-a-service functionality. She likened the current batch list method of acquiring and loading data as extremely dated and inefficient. 

Data providers used to ask us for a sample list of our data, upon which they would then deliver to us the list back of records either augmented with additional info, or some newer records that meet the same criteria.
If you think about it that’s like me walking into a clothing department store, and the salesperson asking me to show him/her my wardrobe and then telling me that these are the clothes that they have to offer me.
I want the full browse, preview experience and the freedom to see and try all the clothes in the store. I want that same experience with data for my business users.

Michelle Goetz, principal analyst at Forrester delivered a keynote that emphasized that business users need to trust their data. And the best way to provide that trust is to give them access to the data, as quickly as possible. And to accept their feedback and input in a collaborative manner. 

Unlike retroactive reports and analytics, data-driven operational applications are one of the best ways to provide this capability, in conjunction with their daily business activities.

Darius Kemeklis of Google presented a session on graph databases and MDM. 

He described how graph databases offer tremendous potential to model and analyze complex relationships inherent in the real world. He pointed out that many enterprises are increasingly considering graphs as a pre-requisite for their MDM strategy.  He provided a foundational tutorial answering questions such as “Is Graph a Concept or Storage Technology?”

Attendees also learned:

  • From successful industry–wide & industry-specific examples of Graph use cases – Darius showed Reltio’s commercial graph as a prime example
  • Where Graph & MDM intersect
  • Key concepts such as building and visualizing graph schemas 

Overall the event represented an industry shift in traditional MDM philosophy. Attendees were definitely evaluating and considering modern data management techniques, and looking to collaborate with business teams to gain their trust, and get their input into continuous data quality through data-driven applications.

From my perspective it was great to old friends and make new ones. We had fun giving away Big Data Lake Crocs and talking data. See you at the next event!

Same Tune Different Song: Leveraging Client Connections in Wealth Management

In my third and final post around how financial institutions can use a configurable data management platform to deploy data-driven applications to understand complex relationships and identify new opportunities, I’m turning the spotlight on wealth management.

Wealth managers can also benefit from data-driven applications to build detailed client profiles, model complex client-to-client and advisor relationships. Their focus would be to assess client lifetime value, increase client loyalty, augment share of wallet, and grow assets under management. Such a data-driven application would allow them to:

  • Build flexible client profiles to manage issuers, investors and syndication groups and track product, industry, region, and investment preferences

  • Aggregate and roll up accounts along household and relationship hierarchies to gain insight into client holdings 
  • Model relationships, including complex organizational structures and professional and personal relationships, to gain insight into centers of influence and six degrees of separation
  • Track all client interactions including call reports, phone calls, meetings, emails, voice notes, financial statements, letters of intent, and pitch books
  • Implement client loyalty programs to manage proactive interactions with top tier clients and analyze performance against service level targets
  • Aggregate sales and asset data at the firm, branch, and advisor-level to target future sales, service, and marketing activities
  • Automate activity plans to improve the efficiency of standard business processes such as account openings, know your client (KYC) updates, and client reviews
  • Automate service requests to ensure timely follow ups and instill advisor loyalty

Data-driven applications have the potential to transform how enterprises in all industries can better serve their customers and uncover new opportunities. The examples I cited in my three posts about financial services are examples of the same capabilities being applied to different use cases through simple configuration. @Reltio our belief is that we can apply data-driven applications to solve the most complex and challenging business problems.

Understand Complex Relationships to Identify New Opportunities

In part two of our focus on data-driven applications for financial institutions, we focus on the need to understand a myriad of complex relationships for identifying opportunities that will allow them to increase their client base and assets under management. Portfolio managers in particular want to develop detailed contact profiles, model complex client and consultant relationships to see who is connected to who, or influences who.  This insight will allow them to better serve current client relationships and gain new prospects.

Specifically they would like to capture information about non-profit clients and prospects, officers, employees, board members, law firms, CPA firms, contractors, and link them together, with activities such as 990 and 990PF tax filings to get a detailed historical IRS data view for each organization.

With this information in one place, they would be able to identify and segmentation non-profits by geography, size of publicly traded funds, and even by CPA firm or accountant employed by that CPA firm.  A data-driven application can provide reliable data management, detailed insights and recommended actions to:

  • Create detailed client profiles to track buy-side positions such as interests, holdings, and preferred sectors and regions to target clients for specific sales campaigns and events
  • View linked tax filings (990 and 990PF) for each organization
  • Model relationships to understand personal and professional relationships and aggregate holdings along those hierarchies  
  • Use connection paths to display relationships between institution team members and target organizations, that may involve friends, business partners, social organizations
  • Enrich information through social media integration to sites such as LinkedIn, increasing knowledge of the team’s contacts and their target connections  
  • Dynamically assign deals to team members based on expertise and automate task assignment by role
  • Track all client interactions including call reports, phone calls, meetings, emails, voice notes, financial statements, letters of intent, and pitch books
  • Collaboratively manage activities by defining coverage teams, managing client interactions, and standardizing sales, service, and marketing activities across the firm
  • Monitor competitor’s clients by tracking assets and competitor deals for any client or prospect

Finding Your Best Prospects … the Ones You Already Have

This is the first of three posts about how data-driven applications can benefit today’s financial institutions. I’ll highlight how an agile data management platform can deliver data-driven applications for any use case in any industry through simple configuration.

More and more, financial services organizations are focusing on driving revenue growth by selling more products and services to existing clients or gaining new clients through the existing client base. Compared to the time, cost, and effort to acquire new clients, this approach makes good sense. It is far more cost effective to market to existing clients than to cold-call names from a purchased list of prospects. In fact, organizations have a 60 to 70% chance of increasing sales to a current client, versus a mere 20 to 40% likelihood of winning back a former client or closing a sale to a prospect. 

Despite the logic, existing clients continue to be a largely untapped revenue source for many financial services companies because there is no enterprise-wide cross-bank/cross-product collaboration that maximizes the value of existing Client relationships.

Firms want to use cross-bank and cross-product referrals to tap into a wealth of opportunity, including:

  • Cost-effective revenue growth
    • Established Client relationships reduce the cost of client acquisition
    • Vast cross-sell opportunities already exist in the Client base
    • Tapping into identified needs results in faster sales with a greater likelihood of closing
  • Longer lasting, more loyal relationships, making it easier to compare and switch providers
    • Studies show that clients who hold more than one product or service with an organization are less likely to defect
    • Users can share appropriate client information from siloed systems across lines of business
    • Deeper relationships make clients feel valued
    • Today’s increasingly sophisticated clientele appreciates a full-service, tailored experience

The role of integrated and holistic client views that cut across lines of business and include an understanding of client relationships along with the in-depth view of the interactions taking place across the organization cannot be underestimated. Coordinating the moving parts of such a level of understanding of current clients can be daunting. Challenges include:

  • Identifying opportunities to sell additional products to a client or household
  • Timely routing of referrals to the right person
  • Ensuring a consistent client experience across lines of business
  • Incenting staff and enabling effective management oversight across lines of business
  • Supporting regulatory and privacy requirements
  • Monitoring key client-instigated actions that carry time-critical implications

A new generation of data-driven applications can allow users in different roles and lines of business to more easily identify cross-bank client opportunities by:

  • Providing a comprehensive client view
  • Enabling gap analysis across the enterprise
  • Tracking client life events
  • Modeling extended client relationships
  • Detecting and report client actions across all channels
  • Meet an unlimited number of use cases across the enterprise through simple configuration

Just like financial institutions, enterprises in all industries should take action now to better engage with their clients before they become someone else’s prospects.