Category Archives: Decision Optimization

Strategy and Innovation Start with Real Analysis

There are two topics this blog always comes back to — decision optimization and spend analysis, and there’s a reason for that. Not only do they both reduce costs more on average than any other technology this blog covers (an average of 12% in the first case and 11% in the second case), but they also improve the quality of decisions, often substantially.

A recent blog post over on the Harvard Business Review on how to “chart a course in strategy and innovation conflicts” did a great job of putting this in perspective. The article, which discussed “east coast” strategy vs. “west coast” design thinking and the “analysis vs. action” schism did a great job of not only pointing out how the best approaches not only come from the intersection, but from the insights that result when a quick and timely analysis can be performed. For example, sometimes you just need to run a quick test to find out if a new pricing strategy will work or if a proposed re-organization is likely to achieve the intended results.

If you have a real analysis solution that allows you to quickly import, cube, slice, and dice your data any way you need it, you can quickly calculate the effects of a new pricing strategy to make an informed decision. And you can quickly analyze how spending would break down across a new organizational structure. A real analysis can help you analyze strategy and spot innovation better, faster, and more cost effectively.

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You Say You Know How To Balance Competing Objectives. Are You Sure?

You need to source some more cocoa for your chocolate factories to keep production moving (and the oompa loompas working). In years past, you’d just hold an auction and cut a contract with the lowest cost bidder, but you can’t do that now that you’re a socially responsible buyer. You can’t buy from some sellers on the Ivory Coast that you know are using child labor, you can’t buy from further away than necessary as long hauls greatly increase your carbon footprint, and you can’t buy inferior products for your luxury chocolate production lines. You can buy some inferior products for your mass economy goods, provided they are blended with higher quality goods, but only so much. You can ship further if the cost is low enough that you can buy carbon credits. And you can source a portion of your award from a select handful of Ivory Coast suppliers who are making an active effort to approve their socially responsible operations.

It’s a complicated decision as you have to balance cost vs. carbon vs. quality vs. brand value. In fact, the only way to truly make the best decision is to use a (strategic sourcing) decision optimization solution that allows for multi-criteria multi-variate optimization that allows a buyer to determine the cost and benefits of various solutions with respect to each objective. In addition, it’s the only way a buyer can truly examine the effect of different weightings of the various criteria under consideration.

While many of the SSDO (strategic sourcing decision optimization) platforms do not yet support this capability, you can be sure that most of tomorrow’s platforms will. To find out what other capabilities are forthcoming in the world of decision optimization, visit BravoSolution‘s website, fill out a short 8-field registration form, and receive your free, exclusive, copy of The Future of Optimization, a new Sourcing Innovation white-paper with groundbreaking insight on eight directions that strategic sourcing decision optimization is likely to take in the decade ahead.

Forget the Champagne – The Real Gift is the Visionary White Paper

In conjunction with the IFPSM (International Federation of Purchasing & Supply Management), BravoSolution just released a brief 18-question survey determined to deduce the current state of sourcing and procurement initiatives globally. If you take just a few minutes of your time to fill out the survey and define the priorities driving your organization’s initiatives, the level of integration that currently exists between your organization’s procurement/sourcing and ERP systems, the applications you currently use, the services you currently use, the benefits you have seen, and the level of value you expect to see, you get entered into a draw to win a free bottle of champagne.

And if you are also willing to fill out an 8-box registration form, you can get exclusive access to the new Sourcing Innovation white-paper on The Future of Optimization!

Even if you are a visionary early adopter who is leading the way in the use of decision optimization who thinks she has a firm handle on where optimization is going, I guarantee you’ll learn a lot from this paper. Even though decision optimization in strategic sourcing has been around for ten years, which would make it a mature technology, in many ways it is still in its infancy. Most solutions barely meet the four pillars that define the basic requirements. Despite the increasing number of players who have started using the term “optimization” in recent years, the doctor still only recognizes six providers as having true strategic sourcing decision optimization solutions. Furthermore, the average solution doesn’t handle complex Bills of Materials, multi-variate trade-off objectives, or true make-vs-buy analysis, which would now seem to be a basic requirement for complex (outsourced) manufacturing. But even this is just the tip of the opportunities iceberg.

So take the survey, fill out the form, get your copy of The Future Optimization, and be the first to get some groundbreaking insight on eight directions that strategic sourcing decision optimization is likely to take in the decade ahead!

Trade Extensions Trades Up its UI … Again

Last fall, I provided you with an update on Trade Extensions and how they traded up their UI across their sourcing suite, making it easier to use while making it easier on the eyes. Well, barraged by constant feedback from users who wanted it to be easier still for the creation of “simple” optimization models, as they transitioned from a “full-service” to a “supported” to a “self-service” model, Trade Extensions decided to trade up its optimization UI again, especially around rule generation and scenario creation.

The Trade Extensions UI and platform was impressive because it’s constraints, or “rules”, are template-based, which permit them to be saved, copied, and applied to any relevant scenario and because it’s filters, which can be used restrict application of the rules, can be defined on bidders, lots, bids, plants, lot fields, and any other defined dimension in the system. Unlike many platforms where the buyer is limited to fixed constraint templates, the Trade Extensions UI allowed the buyer to build her own. However, defining a complex constraint and adding it to the scenario could be a complex multi-step process. For example, if you wanted to restrict allocation to European suppliers to 40% of the total award in Europe and Asia, the buyer would have to:

  1. go to the filters screen
  2. add a new filter that defined the European suppliers
  3. add a new filter that defined the European and Asian locations
  4. go the rules screen
  5. create a new allocation rule that restricted total supply by volume to Europe and Asia by European suppliers to 40% by selecting the rule type, defining the limit, and selecting the filters
  6. go to the scenario screen
  7. add the newly created allocation rule

While certainly doable, the process was cumbersome for simple constraints like “limit the award to The Wonderful World of Widgets to 40%” or “spilt the award between 3 suppliers such that no supplier gets less than 20%”.

In the new UI, which is based on a lot of ingenuity and even more AJAX, you can define the constraint and add it to the scenario from the scenario screen, which lists all the currently associated rules, which can each be enabled or disabled with a single checkbox. Clicking the “New Rule” button brings up a new Rule Creation screen for the scenario which allows you to define a constraint by:

  1. selecting a constraint template from the drop down, which organizes constraints by category
  2. specifying the bounds
  3. adding or defining any required filters on the fly
  4. selecting any required modifiers by way of a drop down

So, in our example above, to define the constraint you’d:

  1. click the “New Rule” button
  2. select the “Allocation (%) to Specified Suppliers is at most X
  3. select the “European Suppliers Filter”
  4. fill-in-the-bound with 40(%)
  5. add the “Restrict To Lot” modifier
  6. select the “European and Asian” lots Filter
  7. save the constraint

Then you’re returned to the scenario screen, with the new rule at the bottom of the list, where you can edit the parameter and filter selections on-screen, as well as turning the rule on-and-off. It makes the creation of even moderately complex rules quick and painless. And if your constraint is complex, or not accounted for in one of the dozens and dozens of pre-defined templates, you still have the classic method where the complexity of the constraint is limited only to the confines of your consciousness.

They’ve also traded up their reporting as well. In last fall‘s post, I told you how they had just released the ability to view scenario results in their new OLAP engine, which is the basis of their spend analysis offering. In the current release, the entire reporting framework has been shifted over to the OLAP engine which not only allows the buyers to slice and dice the award scenarios any way they like, but, with the new report builder, build pretty much any cross-tab, pivot-table, or roll-up report they like on both award dimensions and derived dimensions (which can also be exported to Excel if the buyer so desires).

The UI for defining a new report, which is also based on AJAX, is as simple, and powerful, as the new rule creation UI. To create a new report, the user:

  1. gives the report a name
  2. specifies the bidders, lots, and bids to use, possibly by way of filters (from existing rules) (which can be inverted)
  3. selects the associated dimensions (which can include any associated dimension from the RFX, Auction, etc. such as brand name, division, and historical spend for the lot; name, location, and number of allocated bids for bidders; base currency, date, and bid number for bid)
  4. defines the facts (derived dimensions), such as total spend by supplier; year-over-year savings by category; etc.
  5. selects the scenarios and/or phases to include (which can range from 1 to n), depending on the type of (comparison) report

Plus, the user can also create reports by joining one or more report definitions. If the user wanted to see payment and savings by allocated bidder and the user had a Payment and Savings report and a Allocation per Bidder report, the user can simply run both reports at the same time. The system will calculate the appropriate union of bidders, lots, bids, dimensions, and facts and create the appropriate report.

Finally, they are converting all of the standard reports to templates that can not only be used to run the standard canned reports, but copied and modified to serve your buyers’ needs. It’s an impressive improvement in usability such a short time-frame.

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Optimization: The Only Solution to Complex Spend Management

Today’s guest post is from Paul Martyn, Vice President of Marketing of Bravo Solution.

Paul can be reached at p <dot> martyn <at> bravosolution.com or 312 279 6793.

Most organizations have a diverse spend portfolio that includes many simple, several moderately simple, and a few complex spends.

To address each spend appropriately, we need to understand the dynamics that make each event complex. For starters, let’s look to another ‘multi-faceted’ puzzle; the Rubik’s Cube.

Invented in 1974 by Ernö Rubik, Rubik’s Cube has puzzled generations around the world with its utter devilishness. The multi-faceted nature of the Rubik’s Cube makes for a good analogy to spend management and sourcing.

Read the very interesting Wikipedia article linked above and you’ll find out that a 3×3 Rubik’s Cube has over 43 quintillion starting positions. But, if you know the right combinatorial magic, ANY cube can be solved in 29 or fewer moves. Like spend management, the Rubik’s cube has an extraordinary number of possible starting positions but a logical process (algorithm) can elegantly solve the problem with minimal effort.

Complex Spend Management is another multi-faceted puzzle with even more complexity and ‘faces’ (internal and external to the buying organization) than Rubik’s famous cube. There are many factors which influence decision-making and, like a Rubik’s Cube, each factor of Complex Spend Management is related to the other factors. For example, let’s look at the supplier ‘facing’ decision factors inherent in sourcing decisions; price, incumbency, risk and timing:
If incumbency, supplier risk factors and timing are not important, the spend management puzzle is relatively straightforward to solve. We could use a reverse auction or simple RFI/RFP template and get the cheapest possible price, all other things being equal, pretty easily. This is akin to solving one face of a Rubik’s cube, something most of us have the skills to do.

But, if we are to focus on the multi-faceted nature of our negotiations and explore new, and potentially more efficient, ways of dealing with suppliers while balancing the satisfaction of our internal stakeholders (in operations, finance, marketing, etc) we must recognize how our efforts to solve one ‘face’ or dimension of the puzzle impact the other faces and work to find a solution that satisfies each dimension. We’ve all observed that the price visibility we see in a reverse auction inspires pricing creativity by suppliers. In the same way, if we can offer more visibility into other, non-price stakeholder requirements, we will stimulate suppliers to respond creatively in those areas as well.

Successful sourcing managers find creative ways to drive financial results for their company. Effectively reducing costs means challenging internal stakeholders’ assumptions, preferences, and processes with scenario analysis that quantifies trade-off costs. Buyers need to expand simple price analysis to quantify the total costs (of ownership) absorbed by the operational stakeholders. Complex Spend Management requires that buyers include the inventory and logistics impact in their financial analysis. Buyers are often challenged to explore a wider variety of options to redesign their supply plan while evaluating strategic considerations like ‘make versus buy’.

To address this explosion of complexity, many buying organizations have developed and maintain ‘big ass spreadsheets’ (BASS). BASS were often designed for a single project and then reused on subsequent complex spend events. This approach does not take into account the dynamic nature of Complex Spend Management. The BASS approach is akin to knowing the moves to solve one specific starting position of a Rubik’s cube and applying it to other starting positions – it simply does not solve the ‘new’ puzzle. In short, buyers need a more dynamic and flexible solution.

Fortunately, today’s optimization algorithms provide buyers with a technology that identifies the optimal sourcing solution for each combination of supplier pricing, buyer preferences, business rules and risk factors. This allows buyers to define a problem (starting position) and work with the suppliers in a collaborative manner to propose solutions. The buyers then use optimization to determine which combination of supplier proposals is best.

In essence, optimization technology provides the buyer with the ability to increase collaboration with suppliers and solve any starting position of a Rubik’s Cube by simply pressing the “Solve Now” button.

Thanks, Paul!

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