Category Archives: Technology

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.

There’s No Spend Analysis without the Slice ‘N’ Dice

When I was in Boston, I was lucky enough to spend the better part of the day with Eric Strovink of BIQ, and have a few extended conversations with individuals at some of the local consulting firms that specialize in sourcing, and am now more than convinced that any tool that mandates a single cube, or makes it difficult to change the cube, is not a spend analysis tool, merely a spend data warehouse with built in canned reporting (and, if you’re really lucky, limited ad-hoc capabilities).

Not that there’s anything wrong with a centralized spend warehouse with a consistent view of your total spend, especially one that integrates multiple internal and external data sources and allows you to drill down and understand your spend at a detailed level. Of all the e-Sourcing software tools, it is the one most likely to make your CFO do backflips, especially if it has good reporting (and this is a big if – not all spend analysis tools on the market do), since it makes it really easy for the CFO to tell the CEO where the money is going and comply with all those pesky reporting requirements.

However, the value of such a tool is quite limited to you as a purchasing agent. Now, it’s true that the first time you’ll use it you’ll save big-time, especially if it’s the first time you have visibility into the majority of your spend, but the reality is that this is the only time you’ll see such significant savings. After you’ve identified all of the low hanging fruit identified by the single view provided to you by the system, analyzed each instance of over-spending, and taken corrective actions, you’ll find that you’ll be unable to identify additional savings and the system will simply function as a glorified data warehouse that you only use once a quarter to create those reports for your CFO and check that your teammates our buying off the negotiated contracts – something that you could do almost as well with your existing ERP system and a significantly cheaper Business Intelligence / OLAP tool like Business Objects or COGNOS and some grunt work.

Remember, I’m not saying that traditional spend analysis systems like those provided by e-Sourcing providers like Procuri (acquired by Ariba, acquired by SAP) and Emptoris (acquired by IBM, sunset in 2017) are not without value – if you do not have a good, integrated, data warehouse that integrates your various accounting, purchasing, and inventory systems to provide you a single view of your spend or a good reporting system to produce all of the reports your CFO needs, then you’ll find these systems very valuable. However, it’s important that you understand that the primary value of these systems is in the total spend visibility they provide from a financial viewpoint, not the spend analysis capability you really require to identify potential overspending and cut-costs, because you’ll only be able to do this once – thanks to the single organizational view they are built on. (In other words, you’ll save big when you fist implement the system but future savings will be limited to your capability to quickly catch and stop maverick spend.) So, if you need a system to consolidate your spend data, produce the tedious reports required by all of the new financial reporting requirements, and give you some basic across-the-board spend visibility, or, more importantly, you need a spend data warehouse that integrates with the rest of your e-Sourcing suite, be sure to check these systems out – but understand what they are really worth to you before you sign the check.

In order to help you understand where these systems fail in true spend-analysis, why you need to be able to dynamically create multiple cubes on the fly which support dynamic dimensions, meta-aggregation, cross-dimensional roll-ups, and even federated data sets, I’m happy to inform you that Eric Strovink has agreed to co-author a series of posts outlining what real spend analysis is, how it differs from basic spend visibility, what it does for you, and why you need to get there. Stay tuned. (This series is bound to be as informative as my CombineNet series which, when combined with Paul’s informative posts and rebuttals, is probably one of the best non-marketing filtered sources of information out there on decision optimization.)

aPriori

Last week, in his Spend Management Goes Upstream series, Jason presented the basics of the “aPriori Philosophy”* on Spend Matters [WayBackMachine]. About the same time, I was lucky enough to meet with them in their Concord, MA headquarters when I was in the Boston area.

I must say that I am very impressed with aPriori‘s solution and definitely convinced that their solution is unique. The reality is that if you’re a best-in-class company that has already implemented technology to support the full strategic sourcing cycle, including spend analysis, decision optimization, and compliance (in addition to the old standards of e-RFX and e-Auction), then your only chance for significant cost savings is to attack the design phase – where the majority of your costs are baked in!

This is precisely where the aPriori solution comes into play. If you’re buying direct materials from a contract manufacturer, now you have a solution for understanding precisely what you should be paying based upon precisely computable geometric (physical) cost drivers and related non-geometric (part-related) costs. The reality is that current market value for a part is not always anywhere close to what you should be paying. For example, a sales representative from a new supplier is not incentivized to give you the best deal, he’s incentivized to get the best deal he can for his company. A supplier that’s always made a certain part a certain way might not realize that new technology or materials would allow them to make that part significantly cheaper if they used a different process. In this case, this is primarily due to a lack of insight.

This lack of insight is precisely what aPriori’s tool was designed to address. The application instantly and directly interfaces with your CAD program and interrogates the solid model to construct the geometric cost drivers that aPriori uses to automatically determine all the process routings that can be used to make the part, compute the costs associated with each step based upon standard machine, material, and labor costs, and compute the total cost of each part on a per unit basis by factoring non-geometric cost-drivers such as production volumes, the selected supplier or internal factory selected, and the exact routing and machines used.

This application allows design and manufacturing engineers to understand the cost of a part before they finalize a specification, evaluate different options, and make the best price-performance decision. But this is not the coolest feature. The coolest feature is that the application is based on factories built on mechanistic process models that allow you to configure the application to understand any physical part or factory/supplier you want to analyze and produce an accurate costing model. Once you produce the mechanistic process model, the solution then applies its built in computational geometric algorithms to determine the most cost-effective construction methodology guaranteed to produce the exact part you need.

The aPriori solution is truly a significant advancement in cost-based design technology. As such, not only will I be blogging about it again in the future, but I’ve also invited aPriori to submit a few guest posts detailing some of the advancements in their platform, complementing their forthcoming posts on Spend Matters, and how these advancements will help your organization save a significant amount of money without sacrificing quality or unnecessarily stressing your supplier relations.