Category Archives: Miscellaneous

Enterprise Manufacturing Intelligence

Informance (merged with QlickiT, acquired by Catalyst IT) just released their Enterprise Manufacturing Intelligence Solution for manufacturing companies eager to accelerate improvement initiatives, drive operating strategies, and obtain actionable insight for operational performance.

According to their press release, their EMI solution delivers the top-three critical capabilities required to drive better business decisions:

  • multi-site performance analysis
  • enterprise visibility of production financial performance
  • data aggregation from multiple plant facilities

The solution consists of two modules:

  • Informance Manufacturing Strategist
    • What if Scenario AnalysisEvaluate strategies and the impact on KPIs based on real time data.
    • Bi-Directional Information FlowAllows for the development of strategies and day-to-day operating tactics.
    • Real-Time Performance MonitoringA solid foundation for closed-loop process improvement.
  • Informance Enterprise Alerts
    • Proactive NotificationsAutomatic warnings if the enterprise is in danger of missing a metric at any level – facility, asset, or resource.
    • Dashboard MonitoringManage issues globally from a single access point.

According to Informance, this allows your enterprise to:

  • Unlock Capacity
  • Increase Productivity without additional Capital Investment
  • Reduce Inventory and Labor Costs
  • Decrease Working Capital

since it can now

  • accelerate, sustain, and benchmark operational performance initiatives such as lean manufacturing, Six Sigma, and TPM,
  • drive operating strategies at the executive level into execution tactics at the plant level, and
  • provide intelligence in the form of actionable insight from actual data.

So what is Enterprise Manufacturing Intelligence? According to Informance, it is a strategic decision support system providing real-time visibility and a consolidated view into your entire manufacturing operations with powerful analytics, exception-based alerting capabilities, and integration to enterprise systems to give corporate decision makers control over all aspects of your manufacturing operations.

Whether or not you choose to define Enterprise Manufacturing Intelligence, or EMI, this way is up to you. What I can tell you is that these capabilities are important, since inefficient operations can cost you a lot of money. That’s why I’ve invited Sudy Bharadwaj, CMO & VP of Solutions Consulting, formerly of Aberdeen, to explain to us precisely what Informance EMI is and how it can help your manufacturing organization, or your contract manufacturer, increase productivity and save money.

Forecasting

No doubt about it – despite being critical for effective business planning, accurate forecasting is complex and challenging and still remains elusive for many organizations. However, as the recent issue of APICS Magazine points out in their article “Outlook Warm and Sunny”, one can create good forecasts through the proper combination of judgmental and statistical methodologies and use them to identify new market opportunities, anticipate future demands, effectively schedule production, and reduce inventories.

What’s interesting about this article is that it is well known that neither technique on it’s own can be very effective. Most of us lack the ability to accurately judge future demand due to limitations in human cognitive abilities, the restricted amounts of information we have at our disposal, and unknown causal relationships. Similarly, statistical forecasts are limited with respect to the models they are based on. Although a statistical model is much more accurate than any intuitive model we could come up with, it is built on assumptions and causal relationships which may change over time. The best example of a statistical model gone bad is Nike’s $400M failure in 2000 due to demand forecasting software. Nike relied exclusively on automated forecasts without any judgmental checks, but the newly implemented models were not yet fine-tuned and accurate enough to be deployed in a fully automated mode.

The best forecasts are those that leverage the strengths of both judgmental methods and statistical methods. However, as the author points out, well-established rules must be followed in order to effectively combine these techniques.

The following table summarizes the strengths and weaknesses of each approach.

Judgmental Forecasts
Strengths Weaknesses
Responsive to latest environmental changes

Can include “inside” information

Can compensate for “one-time” or unusual events

 Human cognitive limitations.

Biases
Statistical Forecasts
Strengths Weaknesses
Objective

Consistent

Can process large amounts of data

Can compute many variables and complex relationships

 Slow to react to changing environments

Only as good as model formulation and available data

Can be costly to model “soft” information

Require technical understanding

According to the article, judgmental and statistical forecasts can be combined in different ways to take advantage of their individual strengths but the most popular method in practice appears to be the managerial adjustment of statistical forecasts where managers adjust the statistical forecast in a “managerial override”. Managerially adjusted forecasts can often improve forecast accuracy by including information not available to the statistical model. However, if performed incorrectly, adjustments can cause inaccuracy due to inherent human bias. Thus, established rules should be followed for effective adjustments.

The rules outlined by the article are the following:

Only practitioners with domain knowledge should adjust statistical forecasts.
Judgmental adjustment is more likely to improve accuracy when the adjustment is based on domain knowledge. Generally, only domain practitioners will be aware of the relevant contextual information that should be used to adjust a forecast.
Adjust statistical forecasts when there are known changes in the environment.
The adjustment should compensate for specific events not captured by the statistical model or time series. It should not be based just on intuition or bias.
Structure the judgmental adjustment process.
Use a documented or computationally consistent methodology. This will allow you to repeat successes and insure that failures are caught, corrected, and not repeated.
Document all judgmental adjustments made and measure forecast accuracy.
Records must be kept of all adjustments made, and the reasons therefore, and the results of the forecast must be measured so the process can be improved over time and the underlying statistical models updated when relevant observations are made.

When good, quantifiable, and historical data is available, reliance should be placed primarily on statistical forecasts. Only when the domain practitioners know of relevant contextual events or information not contained in the model should judgment be used to adjust the forecast.

Access Problems?

Some of my southern colleagues have indicated that they have been having problems accessing my blog lately.  I myself have had problems at times, since I host on a remote server, but given the nature of the internet, and the bad weather we’ve had around North America lately, brief outages are to be expected for any site without vast financial resources to pay for replication services.

If you ever have trouble with this blog, or another blog, here is a workaround that might help you (especially if its just a routing issue).  Try accessing the blog (be it Sourcing Innovation, Spend Matters, eSourcing Forum, or Supply Excellence, for example) through Technorati or ProcureIQ – since they both pick up our blog posts regularly.

[Remember, this post is from January 20, 2007, and, as such, it should be no surprise that neither Technorati nor ProcureIQ (no longer in existence) pick up these blogs anymore, especially since only this blog and Spend Matters remain from the original Procurement(-related) blogs.]

Sometimes 80% is enough … (when employing Decision Optimization)

Over on Spend Matters [WayBackMachine] today, Jason put up a shot post titled: “Why 80% is not enough”*.  Of course, I couldn’t leave this one alone, since sometimes 80% is enough.  The comments, which could form a post in themselves, are reprinted below.

Jason:

Obviously not an Optimization Post! Because, with optimization, often 80% is enough! Let’s say you’re operating at 90% efficiency. That says you have 10% to go. If you can achieve 80% of this goal, and get to 98%, and do it affordably (and increase cash flows and profit in the process), that is downright phenomenal regardless of the industry you’re in!!!

For another example, let’s say your primitive spreadsheet model will give you an award allocation that is 80% optimal. Let’s also say that your Platform Optimization Engine (POE), bundled with your cutting edge e-sourcing suite, will give you a solution that’s 96% optimal (80% better than what you would otherwise get). Let’s say this event is for a 10M spend, that the amortized cost of the POE for this event is 20K, and the cost of a one-time use of a Best-of-Breed ( BoB ) solution, guaranteed to achieve 100% of optimality, is 200K. The POE saves you 16% of 10M minus 20K, or 140K. However, BoB won’t save you anything since the 20% of 10M, or 200K, “saved” by BoB is just enough to cover it’s cost, leaving you with a net savings of 0.

In other-words, when you’re talking about Optimization, Often 80% is Enough.

For more insight into decision optimization (particularly as it relates to strategic sourcing), Part VII of my CombineNet Series went up over on Sourcing Innovation today.

Dan:

Precisely. I was referring to a single event, initiative, etc.

The reality is thus: Sometimes 80% is enough, and Sometimes 80% is not even close. It’s all relative.

If you’ve got 80% of spend under management, that’s a big win. (Most companies struggle to get 50%!) But if your total spend is only 80% of optimal, that’s a huge loss.

The truth is the following:
* you need to get as much spend under management as possible
* you need to actively manage it (contract management, compliance management, spend analysis and maverick spend identification, invoice verification, etc.)
* you need to improve your operations constantly
* but you should be satisfied with improvements that close 80% of the gap – you’ll never be perfect at anything, but getting 80% closer to optimal from where you are today is a huge cost savings. Moreover, if you haven’t already, you’ll quickly find out that the 80/20 rule holds in technology too – emerging best of breed solutions that get you 80% closer are readily affordable (e.g. Procuri & Iasta vs. Emptoris & Ariba), but solutions that go beyond 80% improvement are very costly.

So take your 80% win in each category with emerging best-of-breed on-demand offerings, and wait for improvements to come along to get you 80% closer again in the next iteration. (And if they don’t, it’s on-demand, junk it and move to the next on-demand solution if that’s what it takes.)

Consider this: Let’s say I’m spending 500M on acquisitions, and it will cost roughly 10M in on-demand software, systems, and labor to reduce that to 430M where as it will cost 40M for high-end best of breed products and consulting armies to get that spend down to 400M. Which should I choose? The 10M (80%) solution, as it saves me just as much as the 40M (100%) solution: 60M. (500M-430M+10M = 500M-400M+40M)

And that’s why I preach TVM – Total Value Management – based strategic sourcing efforts. Don’t just look at your inbound cost or even your total cost of ownership to produce the product, look at your outbound costs as well. (You have to in turn ship your products to your clients, poor quality will generate returns that will eat away your savings, etc.)

* All posts prior to 2012 were removed in the Spend Matters site refresh in June, 2023.