Existing eRFP systems are based on a simple item or catalog architectures. Simply put, an item is described and a price quote is requested. If there are more items, more rows are appended.
Such systems can be used in two ways: Item Bidding, where every single purchase is bid out as it happens or Catalog Bidding, where the top line items (80/20 rule) of a large catalog of potential future purchases are bid out.
There are many theoretical and practical problems with the pricing approach that this catalog architecture forces upon users. Bidding events that contain multiple items from an overlapping set of suppliers suffer from sub-optimality as combinatorial auctions beyond a few hundred items are numerically impossible.
Episodic bidding of purchases under-leverages the multi-period nature of the buyer-supplier relationship and comes with a high administrative effort that usually leads to low intensity efforts and unsophisticated analysis.
80/20 approaches where the top items are bid out and the tail is assumed to be "ok" are very common but even more problematic. The loss of potential savings from 80/20 sourcing is much bigger than people think. The top items have been sourced multiple times, while the tail is often totally unpriced and vendors take advantage of that. Future specifications change further erodes the savings in the top items, creating an even larger unpriced tail.
The Mitchell Madison Group has spent almost three decades solving these issues for clients by building custom pricing models for specific sourcing categories we encountered. We routinely achieved twice the savings of prior efforts because of the aforementioned dynamic and our solutions outlasted prior contracts because they had pricing flexibility and incentive alignment built-in.
Choosing the appropriate pricing methodology is the key to effective strategic sourcing, as the correct pricing approach maximizes competition, extracts microeconomic information and aligns incentives between suppliers and buyers to innovate. We believe that there are five common generic pricing approaches with two subcategories each that can handle any strategic sourcing categories effectively. This taxonomy is organized in order of disaggregation, i.e. from "Item" (cost for a single specified item) all the way down to "Cost Model" (the recipe for pricing an item).
Multiple buyers, clear and stable specs,
established product markets.
Trivial catalog model upon which most procurement systems are built.
Examples: Office supplies, parts, MRO,
anything with a SKU
A SKU that's unique to a purchase or buyer, i.e. with custom specs
Examples: Custom engineered, military equipment
Spec'ing: Must be appropriate for use cases. Allow vendors to provide alternative specs with financial tradeoffs.
Tail control: Avoid 80/20 application or savings will evaporate.
Ad-hoc competitive bidding for a single purchase transaction. Problematic due to effort and lack of volume leverage.
Appropriate for large, one-off purchases.
Risk is a key part of price, but may be separable into components, e.g.
self-insured healthcare, cat risks, etc.
Example: Most insurance products, health, P&C, etc.
Frequently repeating customer products that can be categorized into mean-stable clusters that can be averaged priced.
Example: Utility services, Legal insurance defence
Disaggregating risk elements and unbundling risk from non-risk components and analyzing synthetic minimum bids and insourcing options.
Categorizing transactions into mean stable clusters and controlling for variance. Risk transfer to appropriate parties. Committed results pricing.
Complex projects with defined outcomes that require coordination / organization of typically high-skilled labor and application of productivity enhancing technology by the vendor.
Example: IT SOW, Advertising Agency services
General contractor type projects with defined custom outcomes, performance and milestones.
Example: Telecom Installations, Construction, Shipbuilding
Prototyping: Use past projects that are good proxies for future work and highly specified as bid objects and obtain underlying "BOM" pricing.
Multi-level pricing: Neither input (hourly rates) or outcome alone are sufficient to control waste and incentivize productivity.
Intermediate output and milestones must be used.
SKU items that in whole or significant part have volatile cost components that need to be indexed.
Akin to trivial cost model pricing.
Example: Paper, commodities, money, nails
Product is unique to a seller (i.e. a laptop) and price differentiation occurs by offering discounts to some buyers off of a private list. Private means that it's published by the vendor only, but usually available to the public.
Example: Servers, routers, most technology hardware
Cascading Discounts: General to specific specifications with increasing discounts.
Agreed upon price lists that are enforceable and verifiable.
Spot pricing overlay in fast moving technology areas.
Indices should be based on actual transactions not surveys and have liquidity and depth.
Use indices with great care. Many are manipulated.
Marked up Labor
Intermediated, marked-up labor
Example: Temps, lawyers, programmers
Apply the recipe for making the product or service and bid out the parameter of the production process instead of the SKUs.
Example: PVC Pipes, furniture, printing
Mark-up should align intermediary incentives with buyers (i.e. inverted mark-ups on role tier / ranges)
Specific Role - Skill - CV match
Competitive industry cost model, not a supplier cost plus model.
Appropriately detailed to gain insights into production economics.
Bid very large purchases also in item format as no cost model is perfect.
Tellingly, existing eRFP platforms are all architected at the top level (Item) so they cannot perform that math required for any of the pricing approaches below, i.e. the more disaggregated methods.
Instead, our MyRFP platform is architected from the lowest level up, i.e. the cost model components that when combined algorithmically compute the bid for a specific item. The MyRFP architecture can handle arbitrarily granular pricing elements and arbitrarily complex algorithms that link bids to practically unlimited baselines in item format to produce instant strategic sourcing decision support analysis.