Too often organizations develop metrics in support of their organizational structures, without taking into account possible system wide conflict.  For example, if the VP Procurement is charged and measured on achieving “lowest unit costs” and the VP of Supply Chain is charged on achieving “lowest average inventory”, conflict will take place since the goals are not compatible.  The buyer will seek larger quantities to buy in order to get a lower price; the supply chain guy won’t want to stock the stuff because it leads to higher average inventory levels.  The business world is riddled with such inconsistencies.  Just ask any sales rep how his managers determines success against his sales forecast!

An enterprise metrics framework seeks to provide an enterprise wide set of metrics that a) support the business goal, and b) ensure no inconsistency in local behavior.  As such, consistency in metrics – their definitions and meaning – is needed if the framework is to be used effectively.  This reads a like MDM!  And so this interesting piece of research formally establishes that link. 

The warning is a small one – but one work mentioning.  From experience, I have heard other people suggest that the definition of MDM should be expanded “because users are applying MDM to all kinds of data”.  I disagree.  We should not redefine concepts and ideas just because they are successful and valuable.  If the practice of assuring consistency and reuse is good, let’s repeat the use of that practice where it makes sense, but let’s call a spade a spade. 

More fodder for overlapping and/or intersecting programs

Interesting this same conversation has been noted in the area of reference data management.  We have not written about this that much, and I have blogged previously on the link between MDM and reference data (nod to Black Watch Data), but some vendors even seek to address a specific task of “mastering reference data for re-use across the enterprise, outside of an MDM program”.  This is a valid need, for some organizations.  However, it might be easier if we refer to “reference data management” as a discrete task; even though in many MDM programs, reference data may need to be included.

Much has been written about “pattern analysis”.  In fact a lot of Business Intelligence (BI) has focused on providing insight to business users to aid in decision making.  However, the classic problem I first mention is more common than we admit.  What if a user is presented with the facts; what if the technology works perfectly – and what happens if the users decide to do something else instead! 

On January 15^th 2011, in the US print edition of the Financial Times, I read an article titled, “Fed misread dangers of housing crash, minutes show”.  The article highlighted how the Fed had been receiving data that clearly showed a bubble in the housing market; worse, the data did suggest misalignment with pricing and risk exposure through the growth in unconventional mortgages.  The data was there; some members of the Fed called out the risk.  But the “collective” decided that the data was not conclusive.  No action was taken.  Disaster was assured.

This is an over simplified blog, I admit.  Of course we have re-interpreted the data and found the issue.  If we knew then what we know now, things would be different.  But the point remains: it does not matter how good our IT solutions are (I include the technology to support an MDM discipline) if our users decide otherwise, disaster can always be assured.  We should never forget that it is the user, the business user that is king here.  We spend a lot of money on trying to understand the predictable outcomes; do we spend enough on trying to understand the unpredictable?  I wonder.

I have written about “rules” in an MDM context before.  How an organization masters rules is not a new topic; analysts have written about (business) rules engines before.  But MDM is bringing a focus to the topic again, in the context of:

• What type of rules are there?
• Who authors such rules?
• How are such rules used?
• If rules or parts of rules (or rule making processes) are re-used, how can this be made effective?

It is the last question that is making users of MDM conclude that rules and MDM need to be related more closely.  And because BI is immersed in rules, the connection between BI and MDM is more important.  A client inquiry brought this connection unto clear focus today with the following description:

“We have been developing BI for many years, and we recognize that rules that adjust data in some fashion exist at many places in our systems, from initial identification, transformation, load, then aggregation, and even ‘post BI’ since users then take data and drop it into a spreadsheet and do more manipulations.”

These rules, in the context of BI, are what constitute aspects of what I call, “passive governance”.  My college, Mark Beyer, would chuckle and correct me with, “Andrew, this is not governance at all” and Mark is correct; I am just a little kinder and I accept that these rules have a job, that is to clean up and process data in a way that should be meaningful to the user/business.  As such, when “active governance” is established (aka MDM) then rules are again created to clean up and process data in a way that is meaningful to the user/business.  The different is that in BI land, these rules are created and managed by IT independent of the operational system; with MDM these rules are defined by business and directly interacting with the operational system.

So the challenge for me is much clearer – after this one dialog with a client – spelled out the obvious.  Over time more and more users will rationalize that they need to apply MDM disciplines to rules that process master data; and also, beyond that, integrity and re-use of those rules, even those that process non master data, can also yield business benefit through more effective management.  The connection between mastery of business rules, and how MDM tools help, will only increase in strength in the next few years.

It seems the Rime of the Ancient Apps Manager/Mariner should be something like:

Rules, rules, every where,

And all the re-use did shrink,

Rules, rules, every where,

And not an object to link.

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…

Then I left home around 7pm to head to the airport.  I decided to take an audio CD my dad had given to me at Xmas – called Forgotten Voices of the Blitz and Battle for Britain.  This was a 3-CD set of recorded interviews with people who had, first hand, experienced the Blitz and Battle of Britain.  For those of you that don’t know, the Blitz was the name given to the time during WWII when the Germans dropped bombs on London and other locations around mostly central and southern Britain, killing civilians indiscriminately.  The Blitz took place largely during the period when Britain stood alone against the Nazi menace.  The Battle of Britain was, of course, a short period of time when “the few” defended “the many” from the Luftwaffe.  Anyway, for 40 minutes I listened intently at the rasping, elderly voices of (mostly) men who had fought and defended Britain in her time of need.  It was remarkable and I arrived at the airport in a strange mood.  The dialog about how the Hawker Hurricanes were physically assembled was fascinating; one chap described it as “dress making” in that chaps would arrive with cloth and string and literally throw the material over the air frame and stitch it together!  Anyway, I have more of the CD to listen to when I arrive home.

Interestingly there was some dialog about how Fighter Command organized the defense and utilized its resources in a tiered structure; I was listening and applying familiar business models to this, using BI, Business Applications, Business Activity Monitoring, Performance Management and so on. 

I came to realize that in order to enhance performance of the entire system (Fighter Command), various aspects of BI had to be deployed, and various aspects of business applications, from strategic, tactical, operation/transactional had to be aligned.  And simulation and optimization was adapted at different levels; and decision making was multi-tiered with several “nerve centers” operating at different levels (Group, Sector, Chain etc).   I thought this would have been a relazing drive to the airport, but the reverse took place.  My mind was working over time and I arrived at the airport my mind was brimming with ideas.  

On the flight I managed to read my Economist (print edition, April 11^th to 17^th) – and would you believe it, I had one of those experiences (the second this year!) whereby several stories just stood out and made perfect sense; and were enjoyable in the process of inwardly digesting the content.  

They key stories for me were: 

• Water Rights – Awash in Waste; “…there is, globally, no shortage of water.  Unlike other natural resources (such as oil), water cannot be used up. It is recycled endlessly, as rain, snow, or evaporation.”  Two articles explore the idea of making a market for water (even though it is seen more as a common/public good).
• Defense Budget – A Daring Punt – read much like what the UK saw with their defense budget not 20 years ago; a slow, gradual decline and change in priorities that, once changed, can rarely be reversed…
• Charlemagne – A surfeit of Leaders; leveraging a slight embarrassing meting with Obama in Europe, the article argues for the rationalization of the European organization since too many daft politicians are let loose on the world. 
• The Federal Reserve – Sacred Territory; alarming article that highlights the moving forces at work in US government that wants to overturn the independent of the Fed for political purposes – we need to know what is happening here and stop it lest the US takes too many steps backwards in economic regulation…  We cannot afford to let the cronies run the place.  And Bernanke steps down next January…
• Malaria – Resistance if Futile; fascinating report highlighting how the traditional approach to “kill off the mosquito” just does not work; every time a new poison is introduced, within a life cycle (some section of the population dies – sure – but another section survives now in the much less competitive market) a whole new resistant strain persists.  The article explains how evolution is being used as a means to understand what part of the overall mosquito lifecycle needs to be “nipped” that would avoid such an effective evolutionary response.  Clever…
• Lessons from Ants – Crowded House – book review for a book I need to get; have read a lot on ants and emergent systems and complex systems; not sure there is too much new stuff here but worth an update and refresher anyway.

After this pleasurable time, I rested for the last 30 minutes of the flight listening to my MP3 player.  And before I knew it, I had some ideas about information management, BI and analytics.  But I am now wondering if these are strange ideas (hence the reference to the Twilight Zone.  After all, I got to the hotel at 11pm and could not sleep for hours!  I had to put pen to paper and didn’t get to bed until about 2am local time.  Now those ideas were inserted into a couple of presentations and research efforts looking at decision making and how to look at information. 

It was a crazy day  one of those that was not meant to end.  I never felt tired, even when my eyes finally closed at 3am.  Ah, the pleasures of being an analyst!

Overall the event was really good.  There were a lot of end users focused on BI and how to get more value from the technology for the business.  Almost all client interactions were focused on this.  Clearly BI has broad appeal, but that link between business perceived realized value and investment remain remains a challenge.  The other Gartner analysts were rushed off their feet – as they tend to be at Gartner summits.  These smaller events, compared to our Symposia, are always more focused on specific topic and so the depth and quality of interaction is always greater – and all the more tiring for it though also more exhilarating (for me at least).

From an MDM perspective, this was a strange event.  I missed the 2008 Gartner BI Summit but had presented on MDM and Performance Management at the 2007 Gartner BI Summit.  Back then MDM was very hot and a lot of attendees wanted to know what MDM was, what it meant to BI and themselves, and how MDM would change or improve or alter BI; for sure, there was not a lot of active MDM work.  I would have assumed that this year, in 2009, with MDM being more widely recognized, that more BI oriented attendees would be “into MDM” more.  However, the majority of clients I spoke with that the event were a) aware of MDM, but b) not active currently, and (more importantly) c), trying to figure out when and where to get started.  So I would assume this means that MDM is more widespread as a topic now, and so a greater audience is looking at it.  But as the prospective audience gets larger, so it becomes clearer that there are many more users who need to “get on board”.  With the very entry level or basic dialog I saw in the user community, it is very important we recognize that though leaders and pioneers might be far ahead in their understanding and use of MDM, the majority of users are not there yet – by a long way.

Off home now – to try to get 3 days of your life back…

• How do users get started with MDM given that it cannot be a ‘boil the ocean’ effort?
• How is success measured?
• What are the best practices to help manage a project?
• What is the reference architecture for MDM?
• How do I identify master data authors in the business?
• Which architectural style is the right one?

I shall (of course) get the pleasure of writing this up in a research note – so I will leave you hanging until I get my thoughts on paper.  However, these were great questions.  Clearly some key themes persist – how to measure value; where to start; what is needed.  Hopefully the responses we publish will help.

Second, I had the pleasure of sitting in on Bill Hostmann’s presentation on “Defining a BI Competency Center to Fit Your Organization”.  This was a great presentation given by an excellent presenter – though you would expect me to say this, I believe it!  Anyway, Bill did a real good job explaining what a BICC is and how it works, and gave lots of anecdotal stories about why it is important and what to avoid when setting one up. 

The key for me however was this: when talking with users about MDM, I am often asked ,”so what about organizing for MDM?” and “what about an MDM competency center?” and I often replay, “use our BICC research but change the name to IMCC to mean information management as the term ‘BI” might convey a too limiting focus”.  I have been saying this for about a year – to many users.  I realize – after seeing the presentation – that a) this is a very good ideas, but b) it is real hard to do since the material is very BI oriented.  So I end up giving myself a “to do” – how to work on some new research note that takes the BICC concept and applies it to MDM.  I will comb through all my client interactions over the last year or so and see if I can get enough ideas down on paper to do this.  Due to workload – could be later in the year.  But I think it is important to do. 

The speakers highlighted how the Summit would explore this discrepancy in order to help attendees make progress in their business, by increasing the value of BI to the business.  I thought the headlines were practical and seemed to offer various guard rails for users to grasp on to.  The part that I thought was missing was the lack of dialog around ‘decision making’.  The focus was very much on the “supply side” of the argument – how to make BI more valuable.  A focus on how and why firms make decisions would have been (I think) more of a “demand side” argument.  However, knowing something about the content (‘wink wink’) I know that the content is there.

Attendance looks good – reportedly over 700 – but the key note was packed with lots of folks standing at the back (including me). 

I had breakfast with one chap – a CFO no less, who said he was here with his CIO and another IT person.  This was a firm that was struggling to build the business case for BI tough he felt they needed the technology.  His goal oriented around how to bight off small parts of BI rather than trying to swallow the whole thing at once.  He went on to talk about how, at source, data quality is a real big issue for his enterprise.  He said, “BI is great, but if you don’t clean the data up first, it wont help much”.  This is true – I think – though for many, BI (and MDM) come with their own dose of “applied data quality”.  I guess you could say that data quality is like oxygen: if you lose it, you suffer.  And not much else works at peak performance when you are in short supply.

Off to coffee break and a client 1-1.