Category Archives: Best Practices

Spend Management – More than an ERP Boost

This summer, Ariba [acquired by SAP] put out a decent white paper titled “Spend Management – A Great ERP Boost that Lowers Costs and Increases Margins” that pointed out that Spend Management complements, enhances, and seamlessly integrates with ERP to enable people, processes, and technologies to improve profitability while reducing risk, optimize the management of global resources, and increase overall competitive advantage while achieving significant operational savings.

The paper pointed out that while ERP may provide the tools to manage transaction processing and financial reporting, it lacks the forward-looking visibility needed to manage costs, support business unit decisions, or plan, budget and forecast spend properly. In comparison, Spend Management fills the gaps and extends the practical uses of ERP to make every day a good day for business. Furthermore, Spend Management is strategic, addressing the larger, mission-level issue of how to spend less as an organization in comparison to ERP [which] is more tactical, addressing the more granular issues of making more efficient spending decisions using control tracking mechanisms.

The paper then states that Spend Management and ERP belong together, and for a simple reason that any organization can easily understand and accept – the unequivocal, incontrovertible need to achieve year-over-year cost savings and increased profitability. Spend Management solutions provide spend data to ERP systems, enabling companies to get a clear, consolidated view of all their spend data, which they can leverage to make better business decisions that drive business improvements and enhance financial performance.

Not bad, but there are at least three obvious problems with this paper:

  1. Spend Management solutions don’t provide spend data to ERP systems, e-Procurement systems and e-Commerce systems do. e-Procurement systems are simply a component of Spend Management.
  2. Neither Spend Management systems, ERP systems, nor their union guarantee year-over-year cost savings, and thus implying that their union addresses the need to achieve year-over-year cost savings is misleading. Remember, there ain’t no saving in a perfect world, and if you’re already more-or-less getting the best price for a commodity, you’re not going to negotiate a better price, especially when energy and raw material costs are spiking.
  3. You don’t need ERP at all for proper spend management!

Let’s address each of these in turn:

  1. Spend Management is the holistic process of managing your spend. It is usually implemented using a set of appropriate supporting technologies, including spend analysis, e-Sourcing, decision optimization, contract management, e-Procurement, etc., but could (theoretically) be accomplished without one or more technological components. Spend data is derived from spend transactions, which are usually accomplished by e-Commerce, e-Procurement systems (also known as P2P or EIPP), or e-Payment systems.
  2. You’ll only get cost savings where there are savings to be had. This is generally true in any category that has not been strategically sourced before, or any category that has not been strategically sourced recently, but not necessarily true in a category that was just strategically sourced for the second or third time. Once you’ve taken all the fat out of the supplier’s margins, built an accurate should cost model, and leveraged all you can get out of your volume, you might not be able to get a better price. Then Spend Management is all about cost avoidance – avoiding, or at least minimizing, the eventual cost increases due to raw material price increases, energy and production cost increases, and plain old inflation.
  3. The paper indicates that the role of the ERP is to make more efficient spending decisions, manage transactions, track information, provide aggregate reporting, and enable visibility. However, efficient spending decisions are made by knowledgeable sourcing professionals enabled by the right technologies that give them the right visibility and decision support, transactions can be managed and tracked by your standard relational database engine, aggregate reporting can be provided by any decent business intelligence tool, which can work off a plain ol’ database just as easily as it can off an ERP, and visibility is enabled by having all of your data in one place, which can be accomplished with any database, business intelligence, or spend analysis tool that supports a data warehouse or OLAP cube.

In other words, Spend Management is an ERP boost, but you don’t need an ERP to get the benefits out of spend management and the tools and technologies that support it. You can not only run all of today’s supporting e-Sourcing and e-Procurement tools stand-alone, but you can even run them on-demand. If you have an ERP, great – you’ve already taken a step to centralizing and normalizing your data in a central repository and you can use that – but if you don’t, no problem. Just get a full suite and use the capabilities of the tools to build your data warehouse. The only pre-condition to adopting spend management is that you have a mindset for cost avoidance. If that’s you, you can start today. Have fun!

Forecasting, Part III

In Forecasting, Part I, I pointed out that accurate forecasting is a complex and challenging problem but that it is generally still possible to create good forecasts through the proper combination of judgmental and statistical methodologies. Specifically, manually adjusted statistical forecasts by an expert who has “inside” information, is aware of “one-time” events, and / or who is responsive to the latest environmental changes can often (dramatically) improve forecast accuracy, provided human bias does not creep in. (Thus, only practitioners with domain knowledge should adjust statistical forecasts using a structured process and only do so when there are known changes in the environment that the statistical model wasn’t really built to handle.)

Then in Forecasting, Part II, I pointed out an article in Purchasing that noted that when it comes to commodity forecasting, judgmental forecasts by experts have the best accuracy on record, demonstrating that expert human judgment applied to good statistical models with solid historical data that also take into account market intelligence and global economic trends are the way to go.

Now I am going to draw your attention to a recent white paper, sponsored by Supply Chain Consultants, by Tom Wallace and Bob Stahl titled Forecast Less and Get Better Results that demonstrates that the conventional wisdom that companies need to project forecasts and plans far into the future at a highly granular level is not necessarily right. Specifically, it points out that detailed forecasts and plans are normally only needed inside of what the authors call the Planning Time Fence or the point in the future when the cumulative lead time to acquire the material and build the product is only a short time away. They argue that outside of this planning time fence, you should only be concerned with aggregate volumes.

Specifically, they argue that up until it’s time to plan a production run, you should only be concerned about forecasting the aggregate volumes required for raw materials beyond the average planning time fence. After all, if you’re a large fast food chain, chances are you can predict with a fairly high degree of accuracy how many burger patties you are going to need over the next year, even if you can’t predict exactly how many Big Burgers, Bob Burgers, or Bo Burgers you are going to sell in any specific week. And if you are a toy manufacturer, chances are you can predict roughly how much plastic you are going to require over the next quarter, even if you don’t know precisely how many units of Dolly House or Trixie Truck you are going to be asked to manufacture. Attempting to forecast to a granular level too far in advance will just mean you’ll constantly be revising your forecasts and wasting time and resources, instead of focussing on what’s truly important for sourcing – the raw material aggregate volume, since that’s where your leverage is.

I’m sorry, but “I’m not omnipotent” just doesn’t cut it anymore!

Integrating Contract Management and Spend Analysis

Today I’d like to welcome back Eric Strovink of BIQ [acquired by Opera Solutions, rebranded ElectrifAI] to Sourcing Innovation. In this post, Eric tackles the contract management – spend analysis integration issue that the sales and marketing representatives of a number of suite vendors often make a lot of fuss about.

If your company is like most, your contracts are a hodge-podge of dense language resulting from hundreds of negotiations, whether you have a Contract Management (CM) system or not. If you already have a CM system, chances are good that most of your contracts aren’t written with the templates and standard language that some of them offer. In fact, most companies use CM systems simply to organize existing unstructured contracts for better searching, reporting, accessibility, and tracking – with the promise, in some CM systems, of proactive alerts.

So when an e-sourcing vendor claims to “integrate” Contract Management with Spend Analysis, exactly what does this mean? Well, as it turns out, it isn’t even necessary to have a CM system in order to integrate your contracts into your Spend Analysis (SA) system.

Let’s imagine that there’s a stack of contracts on the corner of your desk. The “stack” can be a “virtual” stack that’s held in a CM system, or it can be a physical stack of documents; it’s not important which. Each contract represents an ability to buy a commodity or a group of commodities from a specific vendor, over a specific period of time, perhaps additionally limited to a geographical region or a business unit.

Let’s walk through the process of integrating a contract into the SA system.

1) In the SA system, we create a data dimension called “Contract.” It is a simple list of contract names or other identifying information. An entry is defined for each of the contracts in our stack.

2) Using the SA system’s mapping rules, we map potential spending to each contract in turn. The spending on a contract is typically a function of Supplier, Date Range, and Commodity. For example, if contract C174-KELLY was for temp labor, and it was valid between February 2001 and October 2001, and it was with Kelly Services, then we map the combination of

Commodity

Time

Vendor

to the contract:

Mapping

After applying this rule, if we then filter (“drill”) the SA system on the HR>Recruiting>Temps commodity, we see these amounts in the Contract dimension:

Contract

Does this mean that all of the 95,996 Kelly spending was on contract? Absolutely not, since we cannot know (1) if Kelly charged us the correct contract price, or (2) whether someone used Kelly without realizing that we had a contract, or (3) whether in fact anyone ever used the Kelly contract at all when doing business with Kelly. Which is why talking about “compliance” at this level of analysis is silly. But we do know, if we’ve entered all our contracts this way, that the “Other” spending was definitely not on contract. That’s valuable information, and it’s better than half-measures to find bypass spend, such as a “preferred vendor” dimension.

Now, what was the difficult part of the above? Well, it was figuring out what “Commodity” the contract was for, from the perspective of the SA system. Building the Contract dimension is easy (perhaps a vendor’s “integration” logic performed this few minutes of work for you) – but building the rule that maps the contract into the spend cube requires reading the contract and deciding what SA commodity should be referenced. The final work to add the appropriate rule to the SA system? 20 seconds, tops.

Bottom line: It’s easy to integrate contracts information into your SA system. And, with some SA systems, you can embed an HTML link to the contract document itself, directly from the Contracts dimension, to establish a useful reverse linkage.

All without a CM system at all!

Questions to Ask your Optimization Vendor

Not all optimization vendors are equal … and more importantly, not all vendors that claim to have decision optimization even have it (as their systems barely qualify as decision support). Thus, since Emptoris [acquired by IBM, sunset in 2017] just released a new version of their offering, since Iasta [acquired by Selectica, merged with b-Pack, rebranded Determine, acquired by Corcentric] is coming out with their first heavy-hitting release in the next month, and since CombineNet [acquired by Jaggaer] is always working on something new, it’s important that you be able to distinguish between the relative strengths and weaknesses of the different products, as well as how much strength you really need, if good decision optimization is one of your driving reasons for selecting a (new) e-Sourcing solution. (And, by the way, it should be!)

Now, as I indicated in a comment over on Spend Matters (in “Emptoris 7 Pushing the Sourcing Envelope”), I’m not going to devote a post analyzing the new Emptoris announcement at this time, as I don’t yet have enough data points to even make a half-assed*0 attempt (although I do feel I have a pretty good idea precisely what they did based upon their choice of wording, the amount of time they’ve been working on it, and my perception of their in-house skill level), but I really think you should analyze it, just as you should analyze any other vendor’s solution, before buying it. (Not necessarily because I don’t think it will do the job, but because the key with optimization is buying just what you need in the majority of your sourcing events. Optimization is expensive. Buying too much power could severely impact your potential ROI, and buying too little power will be equivalent of flushing that investment down the drain as it won’t solve the majority of your problems. I’m using the word “majority” because there is no general purpose decision optimization product for sourcing that will handle all of your events and solve all your problems. As with just about everything else in business, it’s the 80-20 rule. The best solution is the one that solves as close to 80% as possible at a cost of ownership that maximizes your ROI multiple. You can always do one-time projects with best-of-breed providers or specialist outsource providers for those projects in the remaining 20% where there is enough of a savings opportunity.)

Before I get to the question list, I should point out that it’s almost impossible to cover every question, as many of the questions you should be asking depend on the answers you receive to your first few questions, but I think the question list below is a good starting point. If I get some good feedback, and some more free time, I’ll consider doing a part II at a later date. So, without further ado, here’s the starting list!

  1. Does your product meet the four critera for strategic sourcing decision optimization as outlined in the Strategic Sourcing Decision Optimization wiki-paper on the e-Sourcing Wiki [WayBackMachine]  (initially authored by the doctor, the all-knowing optimization guru*1)? Specifically, does it support the following:
    • Sound & Complete Solid Mathematical Foundations
      such as simplex algorithms and branch-and-bound;
      many simulation and heuristic algorithms do not guarantee analysis of every possible solution (sub)space given enough time, and, thus, are not complete in mathematical terms
    • True Cost Modeling
      many bidders bid tiered bids, discounts, and fixed cost components – the model must be capable of supporting each of these bid types
    • Sophisticated Constraint Analysis
      At a minimum, the model must be able to support reasonably generic and flexible constraints in each of the following four categories

      • Capacity / Limit
        allowing an award of 200K units to a supplier who can only supplier 100K units does not make for a valid model
      • Basic Allocation
        you should be able to specify that a supplier receinves a certain amount of the business, and that business is split between two or more suppliers in feasible percentage ranges
      • Risk Mitigation
        let’s face it – supply chains today are all about risk management, and you should be able to force multiple suppliers, geographies, lanes, etc. to mitigate those risks without specifying specific suppliers, geographies, lanes, etc. to take advantage of the full power of decision optimization
      • Qualitative
        A good model considers quality, defect rates, waste, on-time delivery, etc.
    • What-if Capability
      The strength of decision optimization lies in what-if analysis. Keep reading.
  2. Does it support the creation of multiple what-if scenarios and does it simplify the creation of these scenarios?
    The true power of decision optimization does not lie in the model solution, but the ability to create different models that represent different eventualities (as this will allow you to hone in on a robust and realistic solution), to create different models off a base model plus or minus one or more constraints (as this will help you figure out how much a business rule or network design constraint costs you), and to create models under different pricing scenarios (to find out what would happen if preferred suppliers decreased prices or increased supply availability).
  3. How fast is it for different average model sizes and can performance be tweaked?
    Optimization takes what it takes. That being said, if one solution takes an average of 1 hour for an average scenario, and another solution takes 10 minutes, all things being equal, if you have compressed sourcing cycles, the 10 minute solution might be better. Emphasis on “might”. This is only true if the faster solution is of the same quality – some models, and some solvers, sacrifice quality and accuracy for speed. The best solution will let you trade off “tolerance” and accuracy for speed. Sometimes it’s easy to get within 1% or 2% in a few minutes, even though that last 1% or 2% could take hours. On a model with low total savings potential, getting within 1% may be enough. And when trying to hone in on the right what-if scenario, it’s nice to get within 1% quickly and then allow the right scenario to run to completion over night after you’ve quickly analyzed half-a-dozen scenarios and settled on your preferred scenario. Thus, tweaking ability is very important.
  4. If it supports “real-time” is it “true” real-time or “near” real-time.
    Thanks to significant advances in processor and hardware performance as well as off-the-shelf optimizer technology (like ILog’s CPlex), it’s now possible to rapidly re-build and re-solve moderately sized models using off-the-shelf modeling languages in seconds, allowing for e-auction tools that keep the model relatively small and simple to incorporate decision optimization in near-real-time by simply re-building and re-solving the model every 30-60 seconds (depending on model-size) on a high-powered dual or quad core server with an appropriately configured and optimized CPlex 10. However, this is NOT true real-time optimization and could rapidly break down if the model gets too big or too complex. (For example, real-time optimization requires the ability to merge model construction and model solution in such a way that a new bid can be introduced as a parameter change that does not require the optimizer to rebuild the sparse model matrix and start the solution process over from scratch.)
  5. Describe two or three scenarios you have encountered where you could not model the situation exactly for companies in our vertical, how you worked around the issue, and how accurate the result was.
    No optimization model can handle every real-world scenario 100% accurately. If a vendor representative says so, he’s either lying through his teeth or not competent enough to be selling the product. (Note that: I’ll have our support expert get back to you on that is a good answer from an average sales representative.) This is about the only way to get a decent idea of how appropriate the tool is for you. If the scenarios were complex and the constraints based on business rules you hardly ever, or never, use, then the solution is probably okay for you. If the scenarios were simple and the constraints based on business rules you use all the time, it’s probably not the tool for you.
  6. Can we do a pilot project before committing to a long term license?
    If you like what you hear, but are still unsure, or are having problems getting the budget approved, a pilot is often the way to go! (Note that I did not use the word “free”. You should be willing to pay for services at a rate that is sufficient to cover the provider’s cost for this pilot – especially considering that many of the companies that offer affordable optimization offerings are only able to do so because they keep their costs and overheads down – and if they gave free services away to everyone who requested a free pilot, they would have to increase their costs, and that would be a detriment to everyone, including you, in the long run.)
  7. We’re having problems understanding how this fits into our business or what the best solution for us is. Would you be willing to demo your solution to, and answer questions from, our consultant who understands both our needs and decision optimization technology?
    Let’s face it – just like the right decision optimization tool can deliver huge savings multiples on your investment (10X or more), the wrong tool will simply represent a six (or seven) figure cost that yields little return. If you can’t tell the difference, and there’s no shame in admitting you can’t if you’ve never used this type of technology before, then you should bring in a consultant*2 who can to help you select the right technology, and ensure you are appropriately trained on it, until you are self sufficient and saving an average of 10% to 12% per project put through the tool.

*0 And we all know that any decent attempt should be full-assed!
*1 You should feel free to proclaim my greatness whenever you are not in my presence! I don’t mind.
*2 Just remember that, unfortunately, this consultant may not be able to help you if you want Emptoris evaluated. (And I’m sure that some of you should definitely be evaluating the Emptoris solution.)

Read This Week’s Spend Matters Posts!

This week, Jason Busch has been working like mad to cover Procuri Empower and the Emptoris User Conference and bring you great coverage of not only the events BUT the new offerings these players are releasing. As the only blogger who is capable of diving deep into both of these events, and doing so from a purely independent and objective angle (since analysts have to be careful when the company they’re writing about constitutes a large portion of their firm’s revenue), at least this week, he is the source for those of you who are considering a (new) sourcing solution and want a fresh perspective on these firms.

So even though it might look like I’ve been ripping on him a bit in the comments on his blog this week, I want to assure you that is not my intent. It’s the best coverage I’ve seen in a long time … I’m just trying to push him to go above and beyond what he’s written so far, because, let’s face it, he’s most likely not only the only blogger who can, but one of the few people in the world who can!

Plus, if you comment and ask a question, you will get an answer! How can you beat that? So, go read it – now!

Here are the links* (which I’ll update when he’s done):

Procuri Empower: Dispatch One
Procuri Empower: Dispatch Two
Procuri Empower: Dispatch Three
I feel Empowered
Emptoris Ups the Supplier Performance Ante
Procuri Empower: Dispatch Four
Emptoris 7: Pushing the Sourcing Envelope
Emptoris 7 on the iPhone
The MFG.com Fusion Road Show Rolls On
Comparing User and Partner Bases at Customer Events: Procuri and Emptoris
Procuri Empower: Dispatch Five
Emptoris International User Conference Dispatch One
Procuri Empower Dispatch Six
Procuri Empower Dispatch SevenProcuri Empower Dispatch Seven

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