3 Reasons MDM No Longer Delivers a Customer 360

Today’s guest blog post is from David Corrigan, CEO at AllSight

When Master Data Management (MDM) and Customer Data Integration (CDI) were designed over 15 years ago, they were touted as the answer to “Customer 360”.  But the art of mastering data and the art of creating a complete view of a customer are two very different things.  MDM is focused on managing a much smaller, core data set and aims to very deeply and truly master it.  Customer 360 solutions focus on “all data about the customer” to get the complete picture.  When it comes to a 360-degree view of the customer, master data is only part of the story.  Additional data has to be part of the 360 in order to have a full understanding of the customer – whether that be an individual or an organization. Additional data sources and data types required for today’s Customer 360 include transactions, interactions, events, unstructured content, analytics and intelligence – all of which are not managed in MDM.

Today, leading organizations are looking beyond MDM to a new era of Customer 360 technology to deliver the elusive complete view of the customer.  Here are 3 reasons why

  1. Customer 360 needs all data; MDM only stores partial data.  MDM focuses on core master data attributes, matching data elements and improving data quality.  Customer 360 has rapidly evolved requiring big data sets such as transactions and interactions, as well as unstructured big data like emails, call center transcriptions, and web chat interactions not to mention social media mentions, images and video.
  2. Customer 360 must serve analytical and operational needs; MDM only supports operational processing.  The original intent of MDM was to provide ‘good’ data to CRM and transactional systems.  While a branch of MDM evolved for ‘analytical MDM’ use cases, it was really a staging area for quality and governance to occur before data was loaded into warehouse for analysis and reporting.  A Customer 360 is meant to be analyzed and used by marketing analysts, data scientists as well as customer care and sales staff – it powers many different personas with different perspectives of the customer.
  3. Customer 360 is about improving the customer experience; Master data (core data) is used during a customer experience. Master Data is required during a customer interaction to understand key facts about a customer including name, contact info, account info, etc.  But the Customer 360 needs to blend all interactions, transactions and events into a comprehensive customer journey in order to analyze and personalize customer experiences.

But why does a Customer 360 now require all this information and capabilities beyond traditional MDM?  It is because the expectations of customers and the demands they make on businesses have changed.  Customers want personalized service and they want it now.  And they want a consistent experience across all channels – online, via phone, and in store.  They don’t want to have to repeat themselves or their preferences every time they interact with a business.  This requires companies to know more about their customers and to anticipate their next move in order to retain their business and loyalty.  Because, not only are customers more demanding than ever, but it is also easier for them to switch brands with little to no cost.

In order to meet these demands, many organizations assume they need to build these capabilities on their own using new technologies such as Apache Hadoop and Graph data stores.  These technologies can join together silos of master data, transactional data, raw data lake data, and experience/journey analytics.  However, a new class of software is emerging that bridges data, analytics and action and is based on these modern technologies. Customer Intelligence Platforms manage all customer information and synthesize it into an intelligent Customer 360.  Synthesizing all of those data sources is no easy task and that is where many organizations stall out.  What’s required is a machine-learning contextual matching engine that automates the process of linking customer data and evaluates data confidence.

Organizations such as Dell are seeing this shift first hand and have recognized that legacy MDM apps alone aren’t cutting it.  Deotis Harris, Senior Director, MDM at Dell EMC said “We saw an opportunity to leverage AllSight’s modern technology (Customer Intelligence), coupled with our legacy systems such as Master Data Management (MDM), to provide the insight required to enable our sellers, marketers and customer service reps to create better experiences for our customers.”

If you are like Dell and so many other organizations, a Customer 360 is high on your priority list.  A Customer Intelligence Platform might just be your next step.

MDM not 360

Why IBM Declined to Participate in The Gartner MDM Magic Quadrant

The latest Gartner Magic Quadrant for Master Data Management Solutions was published a month ago as touched in the post Disruptive Forces in MDM Land.

In the section about IBM, there was this note: “IBM declined to participate in this research and did not supply supplemental information. Gartner’s analysis is therefore based on other credible sources, including previous research input from IBM, customer inquiries, Peer Insights reviews submitted during the period covered by this research and other publicly available information.”

My guess is that Gartner and IBM already had a bad relation around the previous report which led to that this report was delayed a couple of months as told in the post Gartner MDM Magic Quadrant in Overtime.

old-school

Recently Nancy Hensley of IBM published a post called Understanding the new Gartner MDM Magic Quadrant and the IBM position. In here Nancy explains that IBM chose not to participate because IBM has a different point of view on where the MDM marketplace is going. In other words: The Gartner MDM market view is old school.

Perhaps magic quadrants, and analyst reports in general, are old school then. Perhaps the new school is that IBM and all the other vendors explain themselves – and can be reviewed by the (professional) crowd. Well, this is the idea behind The Disruptive MDM List.

10 Analyst Firms in the MDM Space

When working with Master Data Management (MDM) it is always valuable to follow the analyst firms that are active on this subject and the related subjects as data quality, data governance and data management in general. You can learn from their insights – and disagreements – on the matters. Here are 10 analyst firms I follow:

Gartner, the large analyst firm known for their magic quadrants, hype cycles and cool vendor lists. There is a lot of brain power in this firm and they have never been caught in admitting a mistake. Quite a lot of posts on my blog mentions Gartner.

Forrester, another firm with heaps of analysts. Forrester has though been less prominent in the MDM world since Robert Karel left for Informatica. However, there are lots of wider insights to gain from as mentioned in the post Ecosystems are The Future of Digital and MDM.

The MDM Institute, which basically is Aaron Zornes, known as the Father Christmas of MDM. Aaron Zornes was the inspirational source in a post called MDM as Managed Service.

The Information Difference, headed by Andy Hayler. They publish a yearly MDM landscape report latest referenced on this blog in the post Emerging Database Technologies for Master Data.

Bloor Group has occasionally made reports about MDM latest mentioned on this blog in the post The MDM Market Wordle.

Ventana Research has been especially active around Product Information Management (PIM) as seen in the press release on their Product Information Management Research.

Intelligent Business Strategies, run by Mike Ferguson. No nonsense, plain English insights from the around the UK Midlands. Home page here.

Constellation Research, the Silicon Valley perspective. Home page here.

The Group of Analysts has published a series of interviews with MDM and PIM notabilities as for example this one with Richard Hunt of Agility Multichannel on Content Gravity.

Aberdeen Group, a company you as a MDM vendor can hire to put numbers on your blog as for example Stibo Systems did here.

Analysts

Disruptive Forces in MDM Land

For the second time this year there is a Gartner Magic Quadrant for Master Data Management Solutions out. The two leaders, Orchestra Networks and Informatica, have released their free copies here and here.

Now Gartner have stopped having a list of vendors on the market too small to be in the actual quadrant. So, if you are looking for new thinking, you will have to read the section about disruptive forces in the MDM market.

Gartner says that every market experiences disruptive forces that influence its overall shape and trajectory over time, and that inspire innovation, both transformational and incremental. According to Gartner, those most prominent in the MDM market appear diametrically opposed.

The current market is dominated by vendors who have predominantly taken a platform-centric approach involving robust technology stacks categorized as application-neutral hub-based solutions. Thus, the business value of the resulting master data is realized through utilization of that data within business applications or suites, or analytics platforms, external to the MDM solution — such as CRM, ERP and e-commerce systems, and data warehouses.

One disruptive force against that is an increase in business applications or suites with embedded ADM (Application Data Management) capabilities that address organizational needs for data management, including MDM (to varying degrees), while also managing nonmaster data for the pertinent application. Gartner states that application-centric approaches for some organizations can return greater value than platform-centric approaches in the short term and do so at reduced cost.

The opposing disruptive force stems from the emergence of more generalized data management solutions. These provide for unified execution logic on top of what is effectively an integrated technology stack. Vendors envision the primary consumption model to be cloud-based subscription. As such, these solutions will also provide a means for midmarket organizations and SMBs to procure advanced data management capabilities (such as MDM) using this model of consumption. Executed crisply, cloud-based subscriptions to these solutions may even moderate the rise of cloud-based MDM offerings.