Keelvar: Not satisfied with the hill, it’s trying to climb the mountain!

The last time we covered Keelvar on Sourcing Innovation was back in 2016 when we re-introduced Keelvar: An Optimization-Backed Sourcing Platform because it was The Little Engine that Could. (It’s last deep dive on Spend Matters was also in 2016, in Jason Busch’s 3-part Vendor Analysis that the doctor consulted on, which can be found linked here in Part 1, Part 2, and Part 3: subscription required. With subscription, you can also check out the What Makes It Great Solution Map Analysis.)

Since our last update, Keelvar has made considerable progress in a number of areas, but of particular relevance are:

  1. total cost modelling
  2. constraint definition for its optimization
  3. workflow-based event automation
  4. usability

After a basic overview of the software, the above four improvements are what we are going to focus on in this article as it is the most relevant to sourcing-based cost savings identification.

Keelvar is an optimization-backed sourcing platform (for RFQs and Auctions) that can also support extensive sourcing automation, especially once a full-fledged sourcing event has been run and a template already exists (and approved suppliers have already been defined). We will start with a review of the sourcing platform.

The sourcing platform is designed to walk a user through a sourcing event step-by-step. Keelvar uses a 7-stage sourcing workflow that they break down as follows:

  1. Design: This is where the event is defined. In this stage you define the meta information (id, name, description, contacts, etc.), the schedule, the RFI, the bid sheet (as the application supports export to/import from Excel for Suppliers who can’t figure out how to use anything except Excel), the cost calculation per unit (for analysis, optimization, and reporting), and basic event settings, especially if using an auction.
  2. Invite: This is where you select suppliers for invitation.
  3. Publish: This is where you review the design and invite list and launch it.
  4. Bid: This is the bidding phase where suppliers place bids. The buyer can see bids as they come in, get reports on activity, and manage the event as needed (extend the deadline, answer questions, and distribute the responses to all suppliers).
  5. Evaluate: This is where the mathematical magic happens. In this step you define item/lot groups, bidder groups, and scenarios. (You need to define groups for risk mitigation and quality constraints, which are impossible to define in the platform otherwise.) Scenarios allow you to find the lowest cost options under different business rules, constraints, and goals.
  6. Analyze: This is where the user can apply detailed analytics across bids and scenarios to see the differences, gaps, supplier ranks, etc. in tabular or visual formats; do detailed analysis on the individual scenarios to understand what is driving the cost or the award; and even analyze the potential awards against RFI criteria submitted by the suppliers.
  7. Award: After doing the analysis and making their decision, this is where the buyer makes their award from either a solved scenario or a manual allocation.

So now that the basics are out of the way, let’s talk about total cost modelling. As per our summary above, that starts with the bid sheet. Either in the platform, or, if you prefer, in Excel, you can define all of the cost components of interest (and even upload starting bid values from the current I2P/AP system and/or previous bid sheets). If you have an Excel sheet that breaks down the bid elements you want to collect, and the totals you want, in columnar format, with enough sample rows, you can just upload it and the platform will not only differentiate the raw data columns from the bidder columns, and map your column names to internal, mandatory, defined columns (for items, lanes, etc.), but differentiate purchaser input columns (such as destination city, country, service/product, etc.) from bidder columns (origin city, country, lane cost, unit cost, tariffs/taxes, etc), differentiate raw columns from formulas, extract the formulas, and even determine default visibility to the bidder (who won’t see the formulas, especially if hidden offsets or weightings are used). The user can, of course, correct and override anything if needed, but for each sheet process, the application learns the mappings (based on user overrides and corrections) and over time has a high success rate on import. Once the columns are defined, editing the column roles (purchaser vs. bidder, visibility, mandatory vs optional, etc. is very easy) – you can simply toggle.

In addition, and this is a major improvement over the early days (when there was no quality control on the coal being used to power that little engine), all of the inputs can be associated with one or more validation rules that can require an input be completed, from a valid set, the same as related bid values, and so on. Out of the box rules exist for easily defining uniform values across a column for a lot (if all items must come from or go to the same [intermediate] location, for example) and requiring complete coverage on a group of lots (critical if a supplier must bid all or nothing on an item, set of related items, sub-assembly of a BoM, etc.). If those don’t work, you can use advanced conditional logic on any (set of) column(s) to ensure specific conditional rules are met, especially if a value or answer is dependent on another column or value. The conditional rule generator uses the formula builder that supports all standard numeric operators and numeric columns as well as string-based matching and type/value based operators for ensuring entries come from an appropriate set of values, possibly dependent on the non-numeric value defined in another column.

In other words, because all cost elements can be defined, because arbitrary formulas can be used to define costs, and because rules can be created to ensure all cost elements are valid, the platform truly supports total cost modelling (which is one of the four pillars of Strategic Sourcing Decision Optimization [SSDO]).

For easy reference, the other three pillars are:

  • solid mathematical foundations, which we know Keelvar has from previous coverage;
  • what-if capability, which has been there since the beginning as Keelvar has always supported multiple scenarios;
  • sophisticated constraint definition and analysis — which was lacking in the past and which we will cover next.

Moving onto constraint definition, Keelvar has made considerable improvements both in the definition of bidder and lot groups and the ability to define arbitrary limit constraints on arbitrary collections of bidders and lots/items. This allows it to address the four categories required for SSDO:

  • allocation: to define minimum, fixed, or maximum allocations for a supplier
  • capacity: to take into account supplier, lane, warehouse, or other capacity limits
  • risk mitigation/group-wise allocation: ensuring that the award is split across a group of suppliers to mitigate risk, that a supplier receives a minimum amount of a group of items to satisfy an existing contract, etc.
  • qualitative: to make sure a minimum, average, quality level, diversity goal (volume-wise) or other non-cost constraint is adhered to

Keelvar has always been great at capacity and allocation but, in the past, it’s ability to define risk mitigation/group-wise allocation was limited and qualitative almost non-existent. But with proper definition of bidder and (item) lot groups, and the ability to define constraints on any numeric dimension (not just cost), one can now define the majority of foreseeable instances of both of these constraints. You can create bidder groups by geography, and ensure each geography gets a minimum or maximum allocation. (And even though you couldn’t define a 20/30/50 split directly, you know the cheapest supplier will get 50%, the most expensive 20%, and the middle one 30% by basic logic. If you wanted a 10/25/35/40, that would be a bit more difficult. But logic dictates the two cheapest get 40%, ensuring the two most expensive get 10%, if you insist each group get between 10% and 40%. A simple total-cost analysis tells you which group should be 40%, which group 35%, which group 25%, and which group 10%. And almost every other group-based allocation you would reasonably want to define would be straight-forward or close with post-scenario analysis.)

Quality constraints such as diversity (by volume), quality (by unit), or sustainably approved (by unit) are also very straight-forward to define. For diversity, simply group all the diverse suppliers and ensure they get a minimum percentage of the volume (by unit cost if that’s your metric) to meet your goals. For quality, if every supplier has an internal quality rating, for each quality level, you can define a maximum allocation that can be allowed for that group to ensure a minimum overall quality level. (And if there was hard data by unit by supplier, you’d just define a hidden column in the bid sheet and define a limit constraint on the quality instead of the cost.) For sustainably approved (by unit), you’d simply group all the sustainable suppliers (instead of the diverse ones) and ensure they received a minimum percentage.

In addition, since we last covered Keelvar, they have incorporated soft-constraint support and made the definition thereof super easy. In the application, you can define a constraint as available to be relaxed if the total cost savings exceeds a certain value. That’s as easy (peasy) as it gets.

This takes us to workflow-based event automation. In the updated Keelvar platform, you can define a complete event workflow, and the platform will automate almost the entire event for you, handling everything until it’s time to allocate the award. Once you create an instance, which is as easy as selecting an event template for activate and defining just a few pieces of meta-data, it will auto-fill / update all of the remaining meta-data (since last time if it was previously run), extract the current, approved, supplier list, automatically request approval from the category owner, publish the RFP (or launch the auction) on the predefined date, automatically send the invites out, collect (and validate) the bids (using the predefined validation rules), run the predefined scenarios when the bidding closes, kick-off the predefined analyses and reports on those scenarios and package them up for the event owner (which can include exports), and take the buyer right to the award screen for scenario and/or manual allocation where the user can make the award if ready, review an analysis, or jump back to a scenario, alter it slightly, re-run it, and then use that modified scenario for the award definition.

In terms of process definition, Keelvar has an integrated visual workflow editor where the user can compose the mandatory steps, conditional steps, and necessary approvals at each step (which could be the category owner, a manager if the estimated event value exceeds a threshold, etc.). Each step can link to an appropriate element which can be completely customized as needed.

However, the easiest way to define an event template, and the most effective way, is to instantiate one off of a completed RFP. The built in logic and machine learning can automatically generate a complete workflow-driven template off an RFP. It can define rules for filling in all definition fields off of a few key pieces of meta-data, define rules for identifying the (recommended) suppliers for future events (for one-click approval by the category owner), suggest publication dates and bidding timeframes, define all of the bid validation rules based on the bid-sheets and defined rules, create default scenario definitions, (re)create default bid/scenario analysis and visualization reports as well as rules to auto-package and distribute exports to the event owner, and even identify the recommended scenario for award allocation.

Once the event template is automatically extracted from the completed event, a user can review it in its entirety and edit whatever they want. And then they know when they next instantiate it, it will run flawlessly. (It’s automation. Not automated. And that’s the way it should be.)

Finally, when it comes to usability, if it’s not immediately obvious, usability has been enhanced throughout the platform. But it’s easier to see it than describe it. So if you want a modern optimization-backed sourcing optimization platform, just get a demo and see it for yourself.

In closing, Keelvar is not just the last standing specialist optimization provider, they’re now one of the best. Let’s hope the next major enhancement tackles true Multi-Objective Strategic Sourcing Decision Optimization On Procurement Tends. (MOSS DO OPT!)