Increase Your Wins With a Cost and Risk PTW Narrative

EconPTW is a highly-accurate Price to Win analysis tool that can be used for every opportunity, at any stage. It relies on proven economic theory, deep PTW experience, and a modern framework that aligns the primary cost drivers and risk factors for a statement of work and creates a logical narrative to isolate and better understand the winning price range. The analytical focus on cost drivers and risk factors also provides insights into the most significant levers (cost drivers) that you can adjust in order to achieve the winning price.

EconPTW’s framework includes locating two important numbers as input towards the final analysis. The first number is an extremely low price called the Fool’s Price™. It’s generated by taking the identified cost drivers to their lowest extremes. It’s a price that fails to mitigate any of the risk factors and would clearly not be biddable. The second number is an extremely high price called the Monopoly Price™. This takes the cost drivers to their high extremes. The Monopoly Price completely mitigates all of the risk factors. It is a price that a Monopoly would offer, and likewise, clearly not biddable.

The two numbers can be determined using various approaches, from a back-of-the-envelope ‘burn-rate’ estimate, to a thorough evaluation of multiple levers. The best approach will depend on the situation. For a quick pursue/no pursue decision, a burn-rate estimate may suffice. For a large and highly competitive final RFP, on the other hand, the evaluation of multiple levers can help uncover opportunities and guide detailed solutioning. EconPTW provides a detailed spreadsheet tool that can help you determine these numbers. You can download the Excel file at no charge by setting up a free account.

The most important cost and risk levers will vary based on the type of bid. Logistics support contracts will have different priority levers than will IT system development contracts, material solutions or combination contracts, for example. Based on the contract being pursued, however, the priority levers are usually quite obvious.

Types of Cost Drivers and Risk Factors

In the EconPTW framework, it’s important to note that the idea is to find the low and high-end extremes. In getting to these numbers, you do not need to consider every possible lever. You can identify and consider only those that will have the most impact. Here are a few levers that our clients often consider in identifying the low-end Fool’s Price scenario and the high-end Monopoly Price scenario.

  • Cost Drivers:
    • Number of staff and work hours—stretching resources to the brink vs. accounting for a more comfortable pace
    • Labor mix/skill levels—using mostly junior talent vs. more senior-level staff
    • Compensation scale/labor rates—paying below market wages vs. above market
    • Make/buy/repurpose—creating the solution from scratch, buying it off the shelf, or reusing something that already exists, such as computer code
    • Subcontractor use—all in-house resources vs. mostly subcontractors
    • Non-recurring engineering (NRE) or other startup costs—No NREs required vs. significant initial investment
    • Supply costs—leveraging lowest-cost suppliers vs. prioritizing other factors over price
    • Inventory carrying costs—designing for no inventory vs. building an inventory cushion
    • Other direct costs (ODCs) such as travel—no ODCs vs. significant ODCs
    • Overhead and G&A multipliers—low like 1.8 vs. higher like 3.0
    • Fee percentage—low like 3% vs. higher like 12%
  • Risk Factors:
    • Requirement details—guaranteed specs vs. allowing for uncertainty
    • Security clearances—expecting no issues vs. accounting for delays
    • Staff performance—assuming perfection vs. allocating for inefficiencies and errors
    • Location of work—no issues vs. allowing for political risk or foreign labor law problems
    • Ability to negotiate lower subcontractor prices—better than expected reductions vs. no reduction
    • Subcontractor performance—assuming perfection vs. allocating for inefficiencies and errors
    • Ability to negotiate lower supplier prices—better than expected reductions vs. no reduction
    • Supplier performance—assuming perfection vs. allocating for inefficiencies and errors
    • Quality of materials—planning for zero quality problems vs. allowing for quality issues and rework
    • Supply chain performance—expecting no supply chain issues vs. calling for warehousing
    • Test program definition—proceeding with low testing vs. thorough testing
    • Commodity/raw material price volatility—expecting no volatility vs. covering for major possible increases or eliminating risk through the presence of a favorable economic price adjustment clauses
    • Contract type—Expecting guaranteed buys vs. unknown quantities (IDIQ)
    • Logistics complexity—planning for easy delivery vs. accounting for high levels of difficulty/risk

Getting to the Fool’s Price and Monopoly Price Scenarios

Once the cost drivers and risk factors have been identified, you simply evaluate each one at the extremes. For example, if labor mix is a major cost driver, the Fool’s Price calculation will max out the use of junior level talent and the Monopoly Price will use nearly all senior-level talent. Neither of these is a feasible solution necessarily, but the process identifies the extremes. These extremes will be used, in part, to calculate the Price to Win. And once the PTW is identified, you can adjust the mix to meet the price needed.

Once you evaluate the extremes for every priority cost driver and risk factor, you end up with the final Fool’s Price and Monopoly Price.

The Fool’s Price assumes minimal costs, accounts for a very low fee, is barely technically credible and includes nothing to cover the risk factors. Again, this is clearly not an actual biddable number, and it would also most likely be eliminated during the government’s proposal evaluation on the basis that it would be not feasible to deliver the statement of work.

The Monopoly Price, on the other hand, uses premium costs, higher fees and has enough resources included to fully mitigate all risks. In this scenario, the government will be paying for anything that could go wrong, including contractor inefficiency and management incompetence. The government evaluators will quickly dismiss this proposal for being outside of the competitive price range.

Comparing Fool’s Price and Monopoly Price

The difference between these prices should be large enough to be meaningful. In general, the gap, (Monopoly Price/Fools Price) should correlate to the number of levers available to be adjusted. The more levers, the greater the gap.

In some cases, the RFP provides the number of labor hours by skill code, leaving only three levers—labor rate, overhead rates and fee. In general, with fewer levers available, your calculated gap should end up being around a 15%-25% difference from the Fool’s Price to Monopoly Price. For example, a Fool’s Price of $10m would have a corresponding Monopoly Price of $11.5-$12.5m.

With a multitude of levers, such as for a robust materials and service solution, the gap should be somewhere between 75%-300%. So a $10m Fool’s Price in this case would have a corresponding Monopoly Price of $17.5-$30m.

Tips and Best Practices

An ideal best practice is to share the narratives for the Fool’s Price and Monopoly Price, along with the estimates, internally with colleagues familiar with the type of work required by the statement of work. This cross-check of cost drivers and risk factors provides another view and will help you make any fine revisions to these extreme estimates.

Finally, don’t over stress about precision at this point. In most cases, a rough order of magnitude estimate focusing on the cost drivers is sufficient. The numbers, when combined with all other inputs, will still generate a very accurate PTW result.

To learn more about EconPTW and sign up for a free account where you can run your Fool’s Price and Monopoly Price scenarios, and develop your narrative, click here.