I was talking with a sales person today who wanted help to initiate a dialog with a client that we knew had an MDM “issue”.  We explored several ways we could help the client with respect to MDM, and as a result of the conversation, the sales person came to a mighty conclusion: why is there not a simple, standardized, blue print for the client to explain to how to get started, and what the next 2, 3, and 4 steps should be?

This is a good question – but I had to explain to the rep what, to me, was obvious.  Each enterprise might end up with a vision and strategy for MDM that seems to look and smell like the next guy, but that is not really important.  What is important, and now clear, is that each and every enterprise starts their journey toward MDM, from a completely different place!  As such, there is no single blue print, but several, even many.  I explained that there were large patterns emerging, but these are today not detailed enough to provide individual blue print for each firm.

There are some typical places from where large clusters of firms have begun their MDM journey; here are some of them:

• Departmental Madness: Specific business leaders, perhaps VP sales and marketing, report that business performance is poor; initiatives to improve customers service, up-sell and cross-sell, are not delivering on their promise despite significant business and IT investment in new application and business intelligence software.  Root cause analysis shows that IT costs are higher than expected in support of increased data cleansing and integration routines; and the business says it takes too long to get the data to make the right decision.  This “departmental” cluster is complicated in that any number of departments might make the leap between the symptom (poor business performance) and cause (master data quality).  So this cluster is actually many different sub-clusters,
• The Unintelligent Business, or, ‘BI gone wild’.  This cluster has the common characteristic that each business meeting, that includes leaders from different parts of the business, spend more time arguing over the data, the source of the data, or the accuracy of the reports they each use, that business decisions are often left unmade, made with poor data, or elevated to senior management who have even less idea what to do about the decision.  Generally each stake-holder has developed, over some period of time, their own data source and this source is independent, and likely not integrated to any formalized information architecture in the business.  This emerged very often when senior executives encourage internal competition for resources and management attention, between departments, or business units.
• The Sunny ERP Uplands: A mid-size firm, in the specialty chemicals industry, is trying to wrestle with a migration from many legacy and custom made business applications to a single instance ERP strategy.  This is a “me too” strategy since the firms’ competitors seem to have done this already, and the firm believe that this is a necessary step in order to remain “in the game’.  There has been little thought to how ERP supports the firms secret sauce, business competitiveness, process automation, or process innovation.  IT has no idea where the master data is; who really uses it, or why.  There seems to be lots of data everywhere, locked up in applications that do not play well with others, will be ‘sunsetted’ over the next couple of years anyway, and bottom line – business and IT do not have a good working relationship.  IT is distrustful of the business – they do not think that the business really knows what it needs.
• The Kaleidoscope: A large, global financial services firm is trying to migrate hundreds of legacy and ERP applications across several regions. around the glob, over the next 5 or more years.  There are regulatory issues to cope with as there is an additional global BI strategy that supports financial reporting.  The final selection of two large ERP alternative vendor is about to be made; the business seems to be ignorant of the fact that compromises in each case will lead to different parts fo the business being serviced with innovative or best in class capabilities. 
• The Engineer: A large, European automotive parts supplier is being hit with two major issues: the need to reduce substantially its time to market for new parts; and increasingly demand and more complex requests from customers and partners for product related data.  The firm has invested in Product Lifecycle Management and this was thought to be the silver bullet to their product development needs; this did not prove to be the case.  While engineering received some good functionality to meet their design needs, the firm seems to be have been over-sold by the PLM vendor that implied that PLM supports the end-to-end lifecycle of the product.  The firm is now wrestling with how to manage information across the business, across PLM, ERP, SCM, CRM, Procurement, and other systems – including trading partners.

You might see aspects of each of these clusters in your business – and that just proves the point.  Every firm will understand and agree that there is value in having consistent master data (we can even agree that need the principles of MDM in the home – every tried trying to change channel without a good, clean program guide?), but the place from which every firm starts the journey is different, and infinitely complex. 

Company A – Two steps forward, One steps back

I met with a number of individuals that represented business and IT, across sales & marketing, operations, finance, IT, and BI.  The customer had an objective of formalizing their MDM strategy.  They reviewed several different initiatives they had underway:

• one focused on finance data consolidation (across multiple ERP systems)
• another focused on building a new “customer hub” for multiple CRM systems, including transactional, master and analytical data
• and a third focused on a data integration pilot that built data quality rules into several data integration flows to clean data up as it flows through.  

This firm also has a longer term ERP rationalization strategy underway.  Over several years they have grown through acquisition, and now represents 5 distinct businesses, in US and Europe, each with their own business systems but sharing common customers, and common suppliers.  

During the dialog the team of users realized that governance, process change, and organization change were keys to making MDM a living, breathing, sustained process.  The projects the team had described had no distinct MDM focus, even though master data was being touched over and over again, with each IT and business initiative.  But with now business sponsor, IT was not able to make MDM “stick”. 

Lastly, we explored why there had not been any MDM focus to date.  We learned that the firm, that is predominantly an information oriented company, had no Information Architect or defined information strategy!   This explained a lot.  Though the firm is profitable (the enemy of innovation), there was no single person or role looking at the overall strategy, let alone master data.  But business pressure was mounting that eventually brought enough users together to realize that MDM was going to be needed – so now the next step is first to establish a broader vision and strategy.

Company B – The Sunny Uplands

This firm is a large engineering firm that has also grown through mergers and acquisitions.  This firm also has several ERP systems, as well as large PLM components.  There are separate sales and marketing business units also.

This firm had developed a comprehensive information strategy even though they are a physical products company.  The products this company makes is very complex (ie engineered) and so a lot technical data is used to design and manufacture – and then support – the product.  This skill has led to a good understand of how to ensure data is maintained consistently, and made shareable. 

Additionally the firm also had developed a series of other master data oriented strategies, across supplier, customer, location, and also other data (called reference data) that looks and smells like master data but is not your typical objects (ie exchange rates, units of measure).

The firm had adopted Gartner’s MDM Maturity Model and compared and contrasted their maturity, across all key business units and departments, all master data domains and initiatives, and evaluated their current maturity against vision, strategy, governance, organization process, metrics, and technology.  The firm presented this information to us and was looking for feedback on the overall strategy: 

• How did the approach look?
• Would gaps in the strategy be found if they continued in this way?
• Were there any obvious gaps now?
• How does their status equate to industry norms?
• What else can they do to assure better success with next steps (execution)?

Bottom Line

These two stories were like applies and oranges – both firms have MDM aspirations, both know that MDM can help their businesses and both know that it is needed.  However, two very important take-aways came to me when I compared these initiatives:

• MDM can succeed in isolation to some larger, information management strategy (such as Enterprise Information Management) but it is real, real hard to succeed with MDM    
• Governance, process, and organization is far more important to MDM success then technology

Busy week – closing out an MDM Magic Quadrant; closing out the MDM Hype Cycle, as well as talking to some users about some complex MDM problems.  What else can an analyst ask for…

There is an obvious question that emerges (that I won’t bother addressing) which is, “is social software just another/latest silver bullet to this problem?”  But the one I wanted to comment on was related: assuming social software can help remove barriers between people so that information can flow more quickly, (in support of improved performance), how does this: 

a)     help ensure that the information shared is actually trustworthy (accurate, complete, semantically consistent, timely, secure, assured etc), and more importantly,

b)     assure that the right information is shared, and sent to the right decision that needs it?

Social software does not obviate numerous issues that hamper business and IT today.  What are the real business drivers that are influencing stake holder performance?  How is the data, necessary to the right decision making processes, discovered and converted into information; and then made executable?  Social software certainly helps improve aspects of the elephant, but it remains an elephant.  Unless firms address the underlying challenges, now amount of a new, adapted trunk will assure the elephant will move on, into the next generation.