Analytics IV: OLAP: The Imperfect Answer

Today’s post is by Eric Strovink of BIQ.

When relational database technology breaks down, as it does on any sizeable transaction-oriented dataset when multiway joins on millions of records are required, the answer is, essentially, to “cheat”. At the risk of dumbing down some pretty complex technology (and the work of some extremely smart people), the usual idea1 is to pre-aggregate totals in advance of the query, so that most of the work of the multi-way joins has been done in advance. This is called “OLAP” — an acronym that is unfortunate at best (“OnLine Analytical Processing”).

OLAP databases solve some data analysis problems, in particular slow joins, but only for certain columns in the dataset, and only for datasets that contain transactional data. So, many of the intrinsic problems of the data warehouse are exacerbated in an OLAP database, because the OLAP database is even more special purpose, and its schema very rigorously constrains the queries that can be expected to work efficiently.

Building OLAP databases is therefore harder than building general-purpose relational databases, and thinking in OLAP terms is also harder than thinking relationally. Deciding what columns are “interesting” is challenging as well, and also time-consuming; by the time the OLAP dataset is built, and you decide the column is “uninteresting”, you may have wasted considerable effort.

But OLAP datasets do provide one major advantage, and that’s the ability to “slice and dice” data rapidly, with visual impact and in human-understandable terms. OLAP viewers give users great visibility into data relationships, and enable exploration of large datasets without any need for IT expertise. That’s primarily what “Business Intelligence” or “BI” tools bring to the party: the ability to navigate OLAP datasets for insight.

So, OLAP solves some problems, but fails to solve others. Here is a short (and incomplete) list of significant issues:

  • A dependence (typically) on a(nother) fixed database schema
  • Another level of schema complexity to manage, in addition to the underlying database schema
  • Another level of inflexibility, in that changing the OLAP database organization is often even more difficult than changing the underlying database schema
  • Another level of complexity in SQL queries (called “multidimensional SQL”, or MDX) must be used, that is much harder to comprehend than ordinary SQL.

In the procurement space, OLAP databases are often used for “spend analysis,” but more on that topic in part V.

Previous: Analytics III: The Data Expert and His Warehouse

Next: Analytics V: Spend “Analysis”

1There are many approaches to OLAP.

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Seven Supply Chain Commandments? I Think One Commandment Is Enough!

SupplyManagement.com recently posted an article on “Command and Supply” which stated that if you apply the seven supply chain commandments to your procurement practice — and ensure its daily execution is faultless — you will achieve superior performance. While I don’t disagree, I think the commandments can be simplified and amalgamated. In fact, I think they can be reduced to one!

But first, the commandments:

  • Articulate a clear value-creation algorithm
  • Approach the supply chain as a comprehensive value delivery system
  • Segment the supply chain and consistently adapt it to the characteristics of each segment
  • Optimize the global operations architecture for scale, access, flexibility and risk mitigation
  • Selectively invest for mastery in differentiating capability areas
  • Deploy information systems that deliver insightful analytics, alignment and responsiveness
  • Drive process execution discipline with the right talent, powered by a culture that enables high performance

They’re all good. But I think this one commandment covers it:

Focus on Value

If you do, you

  • will create a value creation algorithm,
  • focus on the creation of a value delivery system,
  • segment the supply chain into segments which require different approaches for value creation,
  • optimize for scale, flexibility, and risk mitigation,
  • invest for mastery where the returns are greatest,
  • will acquire systems that provide real analytics, and
  • drive for continual improvement in process execution.

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Will CLM, SoW, and VMS Stem the Outsourcing Tide, or Will they Just Accelerate it?

One of the major areas of focus today in services management is the area of Contingent Labour Management (CLM) / Statement of Work (SoW) management, and Vendor Management Solutions (VMS). Big companies with big workforces, and especially big companies that use a lot of temporary labors, contractors, and service providers, not only spend a lot on people, but spend a lot on people who do nothing but manage the workforce — recruiting, hiring, support, project/contract management, layoffs / end-of-contract transitions / firings — as this has traditionally been a very time-consuming and cumbersome process (with all the rules, regulations, and firings, you can literally suffocate under the mound of paperwork you produce).

As a result, many large companies, in an effort to keep the process, and their spend, under control have elected to either outsource entire functions or hand over their management to a Managed Services Provider (MSP) [like Manpower or Kelly Services] that specializes in workforce management processes and can bring best practices and best-of-breed technology to its management. In some cases, it was the company’s only option as their area of expertise did not include staffing and their costs were spiralling out of control.

However, the state of affairs today is not like it was in years past. Modern CLM / SoW / VMS systems are streamlining the process by leaps and bounds, taming the beast, and allowing today’s HR personnel to focus on the people, and not the process. As a result, a task that may have been insurmountable for a small HR team ten years ago can now be easily managed today by that same team with the right technology and training. An organization that once had no choice but to outsource workforce management can now pull it back in house. But will they?

Or will they take advantage of the fact that your average MSP already has this technology employed, and in some cases, has a VMS solution that allows them to manage your workforce while keeping track of their performance. They’re used to it, they’ve trained on it, and they’ve already mastered the current best practices. They can be locked, loaded, and ready to go in a matter of days — as long as you’re willing to give up control.

So will the average organization take back control and bring their workforce management back in house with modern CLM / SoW / VMS systems, or will these systems just accellerate the outsourcing craze and the dominance of the MSPs? What do you think?

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