Category Archives: Technology

CombineNet VII: BoB’s Power Source

Yesterday I told you that not only could CombineNet support all of the basic cost and constraint categories required for true decision support, but that the model they generate accurately represents all of the costs and constraints they support and they can solve the model faster than all of their competitors the vast majority of the time. I also told you that today I’d highlight where this unique capability comes from.

Paul highlighted it in his “Now that’s an Electric Engine …” recent post on CombineNotes [WayBackMachine]. CombineNet’s ClearBox uses sophisticated tree-search algorithms to find the optimal allocation. Furthermore, the algorithms are ‘anytime algorithms’; they provide better and better solutions during the search process. And, CombineNet has also invented a host of proprietary techniques in tree search algorithms, including new branching strategies, custom cutting plane families, cutting plane generation and selection techniques, and machine learning methods for predicting what techniques will perform well on the instance at hand (for use in dynamically selecting a technique).

Even though every model can be built and solved on an off-the-shelf optimizer, the reality is that we are dealing with NP-Complete problems, which means that solve time generally increases exponentially with problem size. This means that for any given solver and any given model class, there is a limit on the average model size that can be solved in any given time window. Although an efficient model formulation combined with an appropriately tweaked off-the-shelf solver can solve a very decently sized problem, one must not ignore the fact that generic solvers use generic algorithms which are not always optimized for the problem at hand. This indicates that it is likely that one could create an appropriately defined custom designed algorithm that is likely to solve the model faster, if not significantly faster.

What is not as obvious is the degree of difficulty often associated with the development of these custom algorithms for strategic sourcing decision optimization. The nature of these problems is that it is very hard to determine for any given solution strategy and any given model instance, whether it is more or less likely to solve the model faster than another similar solution strategy. It’s the fundamental nature of NP-Complete. If we knew how to do it, we’d likely be in P-Space.

As highlighted in the post, CombineNet began to develop its algorithms in 1997, and it has 16 people working on the algorithms. We have tested hundreds of techniques to find those that shorten solve time for Expressive Commerce clearing problems. Some of the techniques are specific to market clearing, and others apply to combinatorial optimization more broadly. And that’s where the strength of CombineNet is – 10 years of research focussed on determining how to solve the combinatorial optimization problems that underlie strategic sourcing decision optimization problems quickly and optimally. Everything else is just icing on the cake.

CombineNet VI: Strategic Sourcing Decision Optimization

We ended our last post by noting that what is important in strategic sourcing decision optimization is:

  1. The ability to support all of the relevant costs and cost tiers.
  2. The ability to support all of the fundamental constraint types required for true strategic sourcing decision optimization.
  3. The ability to generate a model that accurately represents all of the relevant costs and constraints.
  4. The ability to optimally solve the model in a realistic time frame.

Other requirements, which should go without saying, are:

  • Solid Mathematical Foundations
  • What If? Capability

Today we are going to discuss each of these points in detail and explain where the true power of a BoB solution like CombineNet is and what’s just confusing marketing hype.

1. The ability to support all of the relevant costs and cost tiers.

Fundamentally, in order to be a true solution for strategic sourcing decision optimization, the application has to support fixed and variable costs, and, furthermore, the application should allow those costs to be bid in a tiered or layered fashion or as discounts, so that a buyer can use the bidding structures that are natural to the commodity or industry they are in. This includes the ability to define unit costs, transportation costs, usage costs, and impact costs as well as sophisticated supplier discounts along the lines of “If you buy 10,000 forks, I’ll give you a discount on 10,000 spoons”.

2. The ability to support all of the fundamental constraint types required for true strategic sourcing decision optimization.

Fundamentally, the optimization solution must support, at a minimum, four basic categories of constraints: (a) capacity constraints, (b) flexible allocation, (c) risk mitigation, and (d) qualitative constraints in order for it to be a real strategic sourcing decision optimization product.

You need to take into account all of your supplier capacities, you need to be able to account for your current contracts and business rules, you need to insure that sole sourcing risks are addressed when required, and you need to be able to take into account your non-cost requirements such as quality, delivery time, and durability (etc.).

3. The ability to generate a model that accurately represents all of the relevant costs and constraints.

Many solutions exist that let you define whatever you want, but under the hood the costs and constraints are simplified and only an approximate representation is used.

4. The ability to optimally solve the model in a realistic time frame.

This is actually a two part requirement. The first requirement is that the system optimally solves the defined model, and not an approximation of the model. The second requirement is is that the system solves the model in a realistic time frame. A small model should not take more than a few minutes. A medium sized model should not take more than a few hours. A large model should solve overnight. Any longer and the usefulness of the solution is limited, especially when sourcing cycles are now completed in weeks, and not months, and all that a buyer may have to make an award decision is a few days.

Furthermore, as I mentioned in my last post, where CombineNet really stands apart from the rest of the pack is:

3. Their ability to generate a model that accurately represents all of the relevant costs and constraints.

4. Their ability to optimally solve the model in a realistic time frame.

5. Their ability to solve larger models than the majority of their competitors.

Simply put, not only can they support all of the basic cost and constraint categories required for true decision support, but the model they generate accurately represents all of the costs and constraints they support and they can solve the model faster than all of their competitors the vast majority of the time. Furthermore, they have the capability to solve larger models than the vast majority of their competitors. And tomorrow we’ll discuss where this unique capability comes from and why that, and not Expressive-Bidding, Expressive-Commerce, Comprehensive Bidding, or whatever-you-want-to-call-it-today-bidding, is what makes CombineNet BoB.

CombineNet V: Expressive Bidding (in Combinatorial Optimizations)

I know I ended my last post indicating that my next post would put BoB in perspective by extolling the virtues of POE, but I’m getting really tired of CombineNet over-hyping Expressive Bidding and so I’m going to explain why Expressive Bidding and Expressive Commerce has nothing to do with the price of fish when we’re talking about BoB. (Don’t worry, this does not have to be a series of finite length, so I will discuss the virtues of POE eventually so that you can put the virtues of BoB in perspective.)

In Paul’s “2007 – The Year of the Supplier” post on CombineNotes [WayBackMachine], he says Expressive Bids can include conditional (if/then) offers, volume discounts, packages of items (bundles), and other creative offers that take advantage of their strengths and/or recent innovations and with Expressive Bidding, suppliers drive the inefficiencies out of their own business and share the savings with buyers, simultaneously strengthening strategic relationships for long-term supply chain efficiencies and competitive advantage.

First of all, there’s nothing here that you couldn’t do self-serve with MindFlow’s application back in 2000/2001, which was two years before CombineNet started using the terminology and filing for trademarks / copyrights / etc. Secondly, pieces of this functionality existed before that in Emptoris’ offering, FreeMarket’s failed effort, i2’s early technology, etc. Thirdly, operation researchers have known how to do if-then constraints for at least two decades using the Theory of Logical Variables and its precursor instantiations. Fourthly, the same holds true for tiered bids (and every discount can be transformed to a tiered bid with a minimum buy if-then constraint and vice versa), which operations researchers have been accomplishing for even longer using piece-wise linear constraints. Fifthly, these bid styles existed long before the introduction of optimization technology, so there is fundamentally nothing new about what is being supported. Sixthly they’re not the first company to come up with a wizard-like interface (although it looks like theirs may be better than most). I could go on, but you get the point.

I’m not saying that Expressive Bidding, Real-World Bidding, Comprehensive Bidding, or whatever-you-want-to-call-it-today-bidding is not important, it is, because, without it, any optimization application with any degree of sophistication will be quite difficult to use, just that it’s not the greatest thing since sliced-bread, which CombineNet’s marketing materials would leave to believe.

What’s important is:

  1. The ability to support all of the relevant costs and cost tiers.
  2. The ability to support all of the fundamental constraint types required for true strategic sourcing decision optimization.
  3. The ability to generate a model that accurately represents all of the relevant costs and constraints.
  4. The ability to optimally solve the model in a realistic time frame.

Where CombineNet really stands apart from the rest of the pack is with respect to:

3. Their ability to generate a model that accurately represents all of the relevant costs and constraints.
4. Their ability to optimally solve the model in a realistic time frame.
5. Solve larger models than the majority of their competitors.

So tomorrow we’ll discuss these required capabilities and what BoB truly is, and, more importantly, what CombineNet’s offering really is and what is just annoying marketing hype.

On the Eleventh Day of X-Mas (Informance)

On the eleventh day of X-Mas
my blogger gave to me
another vendor hyping,
blog posts worth keeping,
spend vendors lancing,
thoughts for a shilling,
strategies for winning,
tactics for saving,
five golden rings,
four little words,
tri-focal lens,
two boxing gloves,
and a lesson in strategy.

Allow me to introduce you to Informance (merged with QlickiT, acquired by Catalyst IT). A provider of Enterprise Manufacturing Intelligence (EMI) solutions, Informance delivers software and advisory services purporting to enable enterprises to achieve a higher level of supply chain performance with real time visibility and valuable insights into manufacturing operations by addressing the following business areas:

  • Global Visibility
  • Inventory and Replenishment Management
  • Production Efficiency and Cost Reduction
  • Revenue Growth and Capital Investments

These areas are addressed as follows:

Global Visibility
Customizable Performance Dashboard that consolidates information from all global manufacturing facilities and provides real-time information for every product line, down to the factory and individual factor assets.
Inventory and Replenishment Management
A software solution with built-in formulas to allow you to optimally balance cycle time, production efficiency, and production variability from an inventory viewpoint.
Production Efficiency and Cost Reduction
An analysis engine that allows data spanning multiple plants, product lines, and asset types to be analyzed individually and comparatively to allow the discovery of cost-saving transformational improvement opportunities.
Revenue Growth and Capital Investments
The Informance solution tracks utilization levels across the plant network in real time, allowing for real-time order reallocation to insure best usage of capacity and minimal lag time.

The informance platform is designed to support Lean Manufacturing and all that it encompasses, including Total Productive Maintenance, Kaizen, Single Minute Exchange of Dies (SMED)/Quick Changeover, and Overall Equipment Effectiveness (OEE). Now, we all know that Lean (Manufacturing) has been around for a while, and that companies have been selling Lean (Manufacturing) solutions since it has been around, so you’re probably wondering what’s innovative about a company like Informance, especially when lean (manufacturing) is so passé.

Well, even after meeting their CEO earlier in the fall on one of my recent Bay Area trips, I wondered too – but then they simultaneously attracted some of the best marketing and sales talent in the space, including Sudy Bharadwaj, of recent Aberdeen fame, so I took another look – and the answer is simple – usability. Most lean solutions don’t give you enterprise wide visibility, and fewer still are useable. Plus, the new sales, marketing, and business development teams are in the process of revamping Informance’s offerings to make them even more useable and more effective in an average deployment. I know you’re asking what? Why? After all, sales and marketing and business development at most companies exists for the sole purpose of determining how much money can be sucked out of a customer. But you have to understand the caliber and foresightedness of the team that Informance has pulled together. They understand that the best way to make money is to sell a solution that a customer wants – and that’s a solution that solves a problem. Sell them silicon snake oil, and you’ll never sell to them again. Sell them a solution that actually works, and they’ll keep coming back for new and better solutions and services.

So watch out for Informance in the coming year – I think you’ll be hearing a lot more about them.

Spend Matters Not

Not long ago, sometime after my post where I asked Is it the Case that Spend Matters Most?, the posts “Emptoris: Readying the Spend Visibility Armaments for Battle”* and “Ariba: Not Sitting Still in the Spend Visibility Arms Race”* appeared on Spend Matters and generated quite a buzz. I’m now convinced that most of the providers still have not progressed beyond Spend Analysis 1.0 and, more importantly, that spend, or at least the amount of spend, doesn’t matter.

It’s not how much you spend, how you store it, how you cube it, or how you report on it – it’s how much you get, how you profit from it, and how you improve on it. It’s all about value, profit, and continual improvement. The fact of the matter is, sometimes spending more is the right thing to do. If you’re spending more to build higher quality products that allow you to double your profit margins and drastically increase revenue, compared to spending less, building the same products, and having your profit margins shrink to nil because they are not innovative and desirable compared to the rest of the products on the market, then you’ve made the right choice. Just like you should focus on Total Value Management, and not Total Cost of Ownership, when you make your award decisions, you shouldn’t be focused on how much you’re spending when doing spend analysis. It’s what you are spending it on, who you are buying from, the prices you are paying relative to the prices you could be paying and the rest of the market, and opportunities you have to drive value from the spend.

So, how do you figure this out? Analysis. Flexible, powerful analysis that allows you to aggregate, slice and dice, associate, break-out, normalize, aggregate, and slice-and-dice again. Analysis that allows you as the user to see the data any way you want to see it, any time you want to see it, any how you want to see it. A rigid view on a fixed set of dimensions might tell you that you’re spending 30% more on supplier X, but it might not tell you that you’re spending 60% more on servers, 10% more on workstations, and 10% less on laptops compared to other suppliers. In other words, a rigid cube analysis might lead you to conclude that you should be dropping supplier X for suppliers Y and Z, when really you should only be dropping them as a server supplier, aggressively negotiating with them on workstation pricing, and routing more laptop purchases through them for a larger discount.

I have to agree with Eric (Strovink) of biq (acquired by Opera Solutions, rebranded ElectrifAI). It’s the analysis. The value added services, especially those provided by Emptoris (acquired by IBM, sunset in 2017) in their new release, are great, and they can be used to create some top notch reports that will knock the socks off of your stodgy old CFO, especially compared to what you can pull out of a traditional ERP, but that’s not how you drive maximum performance. Drop the spend. Focus on the value. Which supplier is giving you the highest value ratio (the most quality product for the least spend)? On which categories? Why? Which categories are performing the worst? On which categories? Why? Which suppliers do you have multiple contracts which? Any way to leverage the volume? And so on. You need to be able to build a cube, analyze it, slice off dimensions, extract a sub-cube, aggregate the data, run a report, and then compare it to a report generated off of another sub-cube for a different, but complementary, data set.

After all, it all comes down to the bottom line. It’s not what you spend. It’s not the revenue you take in. It’s not your operating costs. It’s how much profit the business makes at the end of the day and the value it returns to its shareholders. And that requires smart spend management based on actionable intelligence – the kind enabled by next generation spend analysis and visibility solutions. Everything else is just reporting – sometimes really, really, really good reporting – but just reporting.

And if the user can’t hack it … then the user needs to be trained or be replaced. Commodity prices are going up. After the third reverse auction, there’s no more fat left to trim. Once you’ve implemented the latest IT system, there’s little room for productivity improvements. That simply leaves collaboration, innovation, and smart spend management.

On a side note, I applaud Iasta for basing their new spend analysis solution on BIQ’s solution instead of trying to build their own from scratch. It takes years to build a good spend analysis solution, and since they are on-demand, they can easily integrate BIQ’s on-demand solution into their platform and extend it with value added services, which is where the real value is. This complements their core strength, the executable sourcing cycle, with a SaaS solution that helps the user determine the best category candidates for dedicated eSourcing events. Furthermore, as time progresses, they can build up baseline cubes and reports for common categories to jump-start the process for new customers and junior analysts. And, since it’s a partnership and not an acquisition, you don’t have one company swallowing another. Although this sounds great in principle, what usually happens is that the development teams merge, the new blended company adopts “one focus”, and a lot of the distinctive expertise that made the acquired company the best at what they do gets masked or disappears. BIQ is going to continue to build a better, differentiated, spend analysis product, Iasta is going to continue to develop better services around the product for the sourcing professionals it serves with its end-to-end executable eSourcing suite, and everyone is going to win. The only thing keeping it from being a perfect solution is the ability to easily integrate 3rd party data sources for spend augmentation and market-based reporting. But I’m sure that will come in time.

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