Wrigley’s Kristen Daihes, Senior Manager of Global Sourcing, presented how Wrigley had used IBM’s solution LogicNet Plus to help with strategic supply chain network design issues.  Such issues are often complex, periodically evaluated, and can result in capital investment activates (such as building, or closing, of plants and warehouses etc.)  Such programs are also very data intensive since complex models of the supply chain, and its possible behavior over time, has to be built.

Kristen described the use of this tool.  She highlighted how fully 60% of the process/project time was spent on “identifying, collecting, and validating data” that is used to model and create a view of the supply chain, while a further 20% was spent actually analyzing the output.  On first pass this might sound odd – why would users spend 3 times the amount of time on “data” and so little on the part that yields the greatest value to the business?

It turns out that the quality of the output (of the model) is highly dependent on the quality of the inputs – the data.  Remember that old adage, “garbage in, garbage out”?  So what kind of data are we talking about? 

• Product, relationships/structures, rules (used on quantity, popularity, affectivity etc.)
• Locations, and all the pertinent constraints (limits, boundaries, throughput limiters, costs etc)
• Lanes, or a representation of how products move from “a” to “b”, and all the pertinent constraints (alternative modes, costs, other constraints, availability etc.)
• Demand (actual orders short term and forecasted demand for many months, even years)
• Resource capacity (suppliers, plants, key bottleneck resources)
• Other data such as calendar, units of measure, currency, tax, duty draw back, etc.

Much of this data is master data: products, parts, and locations etc.  Much is reference data (acts like master data, but not a core entity, such as units of measure, currency conversions etc.  And there are other data that does not fall into either definition easily (such as calendar).  So the learning was this: an affective MDM and broader Enterprise Information Management strategy will help simplify the heavy data management side of such a complex supply chain activity.  

I found it interesting that I took a client inquiry last week that went like this: We see great value in mastering “single view” of master data with MDM – we would like to extend such governance efforts to other data types – how do we go about this?”  There are also many inquiries from users who are trying to establish active governance disciplines as they migrate their business data from legacy to ERP systems. 

This is a worthy question – that seeks to leverage the focus and success of MDM (its discipline) other data that also is shared across the business, but is not a core entity (master data).  This is also a good idea (where sought) but this implies a shift from (only) MDM to a broader EIM strategy.  Enterprise-wide metadata management would be used to manage metadata.  Content Management would be used to manage content.  Enterprise Information Management (EIM) should be used to link all these efforts together and ensure no duplication of effort.

So back to Wrigley presentation…

Another big idea I took away from this very effective presentation was that the quality of data, not just master data, is so critical to many initiatives that relay on data to be shared across enterprises or firewalls.  So much of SCM is like this; so little ERP (HCM, Finance) and CRM is quite like this.  CRM has evolved in this direction in the last few years, but SCM is streets ahead in this regard.  Only Procurement is as close to SCM – simply because procurement and SCM are twin brothers (perhaps CRM is a cousin).  Procurement and SCM have been sharing data with external trading partners for years, far in excess of simplistic transactional exchange.

Another big idea I heard clear from Wrigley’s Kristen was this: before you start implementing any aspect of SCM/SCP, be clear you know what the business question is that is being asked.  She explained that Wrigley had a clear idea of what the business really wanted to evaluate and test in terms of business changes.  Without such clarity, the initiative could have failed.  This is because you will not have guardrails enough to help you gather the right data, and build the right model.  The business won’t know what to do with the data – and won’t relate it to a question, an answer, or benefit.

It was a valuable day out of the office.

Preparations this week focused on getting our last presentations into our editing machine such that they can be formatted, made consistent, and cleaned up for public consumption.  Once the presentations are completed we then begin the slow process if distilling from the key messages, and creating a body of work that is to be published over the next couple of quarters.  Our Summits force us to put on paper all the good, new ideas and content that we have explored with users recently that has not hitherto been published.  These Summits, though a lot of work, are a great way to keep forcing our brains to dump content onto paper, thus freeing up more space for the next set of client interactions.

I had some interesting inquiries this week.  Here is a smattering of the more notable:

On Monday I had a real interesting call with a large industrial end user client that wanted to explore options for – wait for it – “cloud based MDM”!  Well, I knew I was in for an exciting conversation already since that is an odd topic.  I have blogged on this before(SaaS moves the process boundary, does not necessarily change the process, and can make integration of master data more complex); there are not real cloud based MDM offerings today, and really only a very small handful of end users have asked about this – more for interest than anything else.  Only one serious vendor has talked to me about this opportunity – and a credible vendor at that.  But, as I have said before, this is a complex topic.  On the one hand it makes sense that aspects, even all of MDM, should/could go outside the firewall, but the costs to move to that state increase for each and every object.  Those costs relate to integration, synchronization, management and so on.  Application infrastructure gets more complex as a result – until and if enough master data exists outside the firewall at which point the costs, and complexity, fall.  But there must be a tipping point at which this takes place.  Question is – which industry, which business processes, and which master data, are close to that tipping point?  

On Tuesday I had a real good call with an energy user.  This was a large organization with a strong IT shop; I spoke with several senior architecture folks were trying to invigorate their overall information management (IM) strategy.  They knew that MDM played a role in overall IM but they were not totally clear what the relationship was; and they also had an issue with “getting started” – how could they get interest from the business to help them with their IM strategy?  We explored MDM and its connections to IM, as well as to Business Intelligence and Business Applications, and very quickly the client realize that MDM is a great place to start their IM invigoration efforts!  I suspect that I will be talking with them a few times in the next few months to help guide them through their MDM launch.

On Wednesday I presented on MDM vendors to our MDM Special Interest Group (SIG) that is part of our EXP program’s Best Practice Council.  I highlighted the lenses through which we look at the MDM landscape (data domain, use cases, industries) and then talked about how the vendors align both in terms of capability, versus direction.  Many vendors are “good” at one thing/area, and have plans to be “good” at many others.

On Thursday I had a call with an end user firm that I know very well.  In a previous life I worked for an organization that had a business relationship with this client, so I knew something about their business.  They are in consumer goods/fine chemical industry segment, and they are struggling with one aspect of MDM – that being the link between MDM and product design/development, clinical trials, and operations/manufacturing.  The client has a lot of experience with operational MDM for traditional objects, such as customer and product, but this aspect of MDM was more focused on multi-enterprise considerations of sharing complex and confidential information that drive product design, development and acceptance.  

On Friday I joined one of our more interesting virtual research communities (B2B) that span several other formal communities, to explore how business to business is evolving.  My interests, including Supply Chain Management (SCM), concerned both the drivers for why business processes are moving outside the firewall, and with Master Data Management (MDM), what are the barriers and inhibitors to that movement. By exploring one specific phenomenon, related to e-Invoicing, we concluded that we need to identify scenarios by which users can evaluate a longer term B2B strategy.  You might not see the connection – between e-Invoicing and long term B2B strategy – but it is there.  More on this later…

So it was a great week – brimming with client interaction, and research production.  Time for a rest, and a cold one.  Have a good weekend.

After reading my interesting email, I then turned to my Financial Times and there, on the front page, was the same article from Panjiva.  The head line read, “Slump in US clothing sales leads to 70% fall in overseas suppliers.”  The fascinating article, referring to the same source in the email I had received, reported a reduction in total volume, and number of suppliers (70 per cent between July to October 2009), servicing buyers of apparel products in the US.  Of those suppliers shipping, they report a reduction in volume of at least 75 per cent.  This is frightening data that highlights how the results of the credit crunch are winding its way through the economy.  No wonder many manufacturers are ramping up with their cost cutting efforts.  

Ignoring the actual content, Panjiva is an interesting vendor.  The value proposition is innovative.  By sniffing data that is effectively public (you have to pay the US Customs a small fee to buy the data, every day) and applying specific metrics and analytics the vendor has been able to interpret dumb data and infer business trends that help business users make smarter decisions.  The vendor is now building a business by selling their inferences and insights back to the buyers, and sellers, to help them look for new and better opportunities to improve business.  This is not quite an MDM play, but certainly a neat play on finding value from information that has been around for a long time.

Don’t forget to look at Gartner’s initiative to help IT cut business and IT costs.  We have lots of research that addresses many aspects of the business that you should be leveraging.  

There is NO WAY the US government should bail out excessively poorly performing firms (remember – this is my opinion, so I can say this).  Firms like GM, Ford and Chrysler, have been dying slowly for many years.  There is no universal agreement what the cause was – if indeed there was one – but certainly there are observations that reinforce that there were major issues some time back.

Did the Big 3 make the wrong cars?  Did they spend too long living off their laurels with profitable high margin “big cars” and take too long to develop or seed the US market for smaller, more efficient cars?  Do they blame this situation on “we do what our customers tell us” rhetoric?  Did the automakers model risk through their entire end to end supply chain process in order to streamline costs?  Did they just pay their employees too much and for too long, and now are hamstrung by unions?  Did these firms have a single business process platform on which to model single view of customer, product, supplier, in order to propagate new product data, new competitive process models?

I don’t know the details but I do know this: if management is making the wrong decision, no amount of IT will help.  Certainly IT can help enable better decision making: MDM can help in unifying the underlying data that is consumed in decision making processes; SCM technology can help model and evaluate what happens to decisions if conditions (think inflation, currency exchange, constraints) change.  Even product portfolio management can help evaluate which markets should be addressed and at what price and desired margin.  But this requires management to lead, and recognize the value that IT can bring to the business.

Earlier this year I was in Detroit and I visited a very large parts supplier.  This parts supplier had many manufacturing locations, and it had outsourced much of its IT strategy and IT management.  IT was outsourced some time ago since it was felt that IT was not the parts maker’s core competency.  The result however is that the gap between process adaptation (a business competency) and business application deployment (a perceived IT-only competency) became so great, that it took even LONGER for the business to adapt itself to changing business conditions.  

I was flabbergasted to discover that the entire business planning process, from annual financial planning down to factory floor level parts demand forecasting, was all run on  spreadsheets!  And this condition had remained in place for several years even after this firm had spent millions and millions of dollars on IT, over many years to “automate the business”.  What on earth where they doing with IT?  It was incredulous to me that this well known, hitherto successful firm, was now too cash strapped and too near death’s door, and bereft of any idea how IT can help business, that it had no capacity or ability to change.  IT had been excised from the body and what seemed like a good decision at the time (“we saved some money since we pay a specialist that is more efficient at running servers”) turned out to be yet another seed that contributed to the demise of the overall US automakers industry.

If the Us government bails out the “Big 3 it will be my taxes that will be used to sustain an over paid, bloated, inefficient, and poorly led industry.  It’s about time the chickens came home to roost: Chapter 11 is what is needed.  It’s a shame, but in this case it is probably too late for technology to help here.  

If you have not read Micheline Maynard’s, “The End of Detroit”, I would recommend it.  I suspect that it will be updated (it was written in 2003).  It’s a good “who done it” type read that describes one view of how Detroit sowed its own seeds of destruction.