Category Archives: Guest Author

Looking Behind the Knowledge Network Curtains

Today’s guest post is from John Shaw, the Director of Education Services for Supply Management at BravoSolution.

In a recent post, the doctor asked, “Where is the Knowledge Network?” and “What is an aspiring supply management professional to do?”

Our industry is offering a growing list of online resources and supply management organizations. We can use these resources to augment the knowledge we gain through our professional activities and personal networks. As the doctor stated, each of these resources takes time and effort to build, so naturally, the goals and objectives of these networks are aligned with those individuals who invest in building each network in the first place.

Our challenge as supply management professionals is to navigate this forest of information in a way that maximizes our personal development. To do so, we need to understand where our personal objectives align with those of a knowledge network. The better we understand how each network’s objectives align with our own, the more value we will receive out of the limited time we have to invest in them.

So as both a consumer of these networks and a developer of some (see discloser below) I’d like to offer some questions for you to ask when trying to determine if participating in a particular knowledge network would be valuable to you:

  • Does the intent of the network align with the needs of the membership?
    The Network Guidelines should clearly state the audience, and the types of information exchange the network facilitates. If they are not stated, or they do not align with what your current development needs, your time may be better invested elsewhere.
  • Who are the thunder lizards?
    Look to see who the most active participants are. The most active people in a community will steer its direction. If these people are your peers, or better, if they are in roles that you aspire to, look further into participating.
  • Who is in charge?
    Successful communities are driven by the membership. If enough thunder lizards march in the same direction a community will move and take a life of its own. The builder can find him/herself in the passenger seat. In the best scenario, you’ll find that the thunder lizards are your peers, and they are in charge!

So what are we to do? Unfortunately there isn’t a simple answer. Whether we are learning about supply management, following politics or trying to get the best advice online for fixing a leaking pipe, we need to look behind the curtains to understand our information sources

Thanks, John!

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Analytics VI: Conclusion

Today’s post is by Eric Strovink of BIQ.

I’ve suggested previously in this series that analysis doesn’t have to be done by an applied mathematician; the key is to get insights about data. Sometimes those insights do require rigorous statistical analysis or modeling, to be sure. Much more often, though, one simply needs to examine the laundry, and the dirty socks stand out without any mathematical legerdemain.

Examining the laundry requires data manipulation. This usually takes the form of data warehousing, i.e. classic database management technology, extended in the case of transactional data to OLAP (“Online Analytical Processing”), SQL and or MDX, and reporting languages and tools. Problem is, business data analysts typically have insufficient IT skills to wield these tools effectively; and when they do have the skill, they seldom have the time. Thus, ad hoc analysis of data remains largely aspirational.

Custom data warehouses have value for organizations. ERP systems are a good example. But the data warehouse is a dangerous partner. It is not the source of all wisdom. It cannot possibly contain all the useful data in the enterprise. Warehouse vendors have trouble admitting this. For example, for years ERP sales types claimed that all spending was already tracked and controlled by the ERP system, so there was no need for a specialized third-party “spend analysis” system. These days all the major ERP vendors offer bolt-on spend analysis.

Spend analysis has the same issue. It introduces another static data warehouse, an OLAP data warehouse, along with data mapping tools that are typically not provided to the end user. As above, the data warehouse is a dangerous partner. It is not the source of all wisdom. It cannot possibly contain all the useful spend data in the enterprise. Spend analysis is not just A/P analysis; it can’t be done with just one dataset; and it’s not a set of static reports.

Once an opportunity is identified, more analysis is required to decide how to award business optimally. The Holy Grail of sourcing optimization has been a tool that is approachable for business users; but this goal has proved to be elusive. The good news is that “guided optimization” is now available from multiple vendors at reasonable price points. Although optimists (mostly experts at optimization) have argued for several years now that optimization is easy enough for end users without guidance, I take the practical view that it doesn’t really matter whether that’s true or not. As long as optimization is available at a reasonable price, whether it has a services component or not, the savings it delivers are worthwhile.

By no means is this series an exhaustive review of data analysis. For example, interesting technical advances such as Predictive Model Markup Language (PMML) are enabling predictive analytics to be bundled into everyday business processes. Scenario analysis is also a powerful tool for painting a picture of potential futures based on changes in behavior. But the vendors of these technologies either must make them accessible to end users, or offer affordable services around them. Otherwise they will remain exotic and inaccessible.

The bottom line is that analysis tools must be accessible to end users. It must be easy and fast to build datasets and gain insight from them. Optimization software should automatically perform sensitivity analysis for you, as the doctor has advocated. Ad hoc analysis should be the rule, not the exception. Analysis should not require vendor or IT support; if it does, it likely won’t happen.

The more you look, the more savings you will find; and when you walk into the CFO’s office waving a check, you will get attention as well as the resources to find even more.

Previous: Analytics V: Spend “Analysis”

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Procurement – Why we really matter!

Today’s guest post is from David Furth, VP of Marketing at Hiperos. David has been in Procurement for over 20 years and has held senior positions at Perfect Commerce, BasWare, RightWorks/i2, and Deloitte Consulting.

Procurement is on the verge of experiencing its next major transformation. During the past ten years, the emphasis has been on optimization – leveraging spend, improving the sourcing process, and becoming more efficient across all aspects of the P2P and Order-to-Cash value stream.

As a result of these improvements, companies now rely on suppliers, outsourcers, and other third parties more than ever. A fact now recognized by C-level executives, boards of directors, and regulators, alike. Why? The increased reliance on these third parties has occurred without implementing the same level of control or having the same level of visibility that was in place when the work was being performed internally. The result is increased risk to company performance and brand reputation.

As a result, forward-looking procurement leaders are transforming their organizations. They still maintain the same obligation to keep costs down. But they have added the responsibility to continuously assess risk, pre- and post-award, and introduce integrated processes and controls across their companies to mitigate that risk by working closely with other functional areas, business lines, and geographies. During the next few years, procurement will be looked upon to provide important guidance around how key external contributors to their companies’ value chains are managed.

This is why more and more procurement executives are stepping forward to introduce a consistent method for managing providers across a wider breadth of their extended enterprise. These executives recognize that just because the contract assigns responsibility/liability for just about “everything”, this does not absolve their companies from the responsibility of ensuring each provider is living up to all contractual obligations. This requires implementing management control programs that actively monitor both performance and compliance to help ensure suppliers are meeting all their obligations.

This is an enormous responsibility that requires consolidating requirements across a large number of stakeholders, communicating expectations to all providers, collecting information and documentation about current status, and collaborating with providers to remedy issues when shortfalls are identified.To be successful requires a new attitude, a thoughtful approach, buy-in from key stakeholders, and the appropriate technology. Despite the best of efforts, responsibility or risk cannot entirely be outsourced.

So, when you consider the consequences of suppliers failing to meet their obligations, regulators handing out fines for poor oversight of third parties, and investors losing confidence in your brand, it is not surprising to see real action taking place. The past few years have made it abundantly clear, it is not a good strategy to expect that a great contract will get you great results, ensure providers follow the law, or prevent them from acting unethically. Therefore, it is imperative to have the appropriate level of controls to mitigate to the appropriate level of risk. This has not been the traditional way of thinking, but that is rapidly changing.

Thanks, David.

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Analytics V: Spend “Analysis”

Today’s post is by Eric Strovink of BIQ.

As an engineer who originally entered the supply management space in 2001 to build a new spend analysis system, over the last 9 years I’ve watched marketing departments consistently “dumb down” the original broad and exciting definition of spend analysis that I remember from those days, to something really quite ordinary. For example, here are the steps required for classic data warehousing:

  1. Define a database schema and a set of standard reports (once, or rarely)
  2. Gather and transform data such that it matches the schema
  3. Load the transformed data into the database
  4. Publish to the user base
  5. Repeat steps 2-4 for life of warehouse

And here are the steps required for what has come to be termed “spend analysis”:

  1. Define a database schema and a set of standard reports (once, or rarely)
  2. Gather and transform data such that it matches the schema
  3. Load the transformed data into the database
  4. Group and map the data via a rules engine
  5. Publish to the user base
  6. Repeat steps 2-5 for life of warehouse

Not much difference.

You might ask, how can spend analysis vendors compete with each other, when the steps are so simple, and when commodity technologies such as commercial OLAP databases, commercial OLAP viewers, and commercial OLAP reporting engines can be brought to bear on any data warehouse? Well, it’s been tough, and it’s especially tough now that ERP vendors are joining the fun, but they compete in several ways:

  • Our step 4 is better [than those other guys’ step 4].
  • [briefly, until it failed the laugh test] Our static reports are so insightful that you don’t even need anyone on staff any more.
  • [suite vendors’ (tired) mantra] “Integration” with other modules
  • “Enrichment” of the spend dataset with MWBE data, supplier scoring on various criteria, and any other ways that might exist to try to add checklist features for analysts that may broaden interest in the spend analysis dataset beyond simple visibility.

It’s all very discouraging, but the doctor and I will continue to point out that spend analysis is not just A/P analysis; it can’t be done with just one dataset; and it’s not a set of static reports or a dopey dashboard, even though some vendors and IT departments would like to think it is. Spend analysis is a data analysis problem just like any other data analysis problem, and it requires extensible and user-friendly tools that empower people to explore their data for opportunities without third-party assistance. Those data come from multiple sources, not just the A/P system; many datasets will need to be built and analyzed; and from them, hugely important lessons will be learned.

The above notwithstanding, building a single A/P spend cube is a useful exercise. If you’ve never done it before, you will find things that will save you money. But that’s just the tip of the iceberg.

Previous: Analytics IV: OLAP: The Imperfect Answer

Next: Analytics VI: Conclusion

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