2Is Inc.

Case Studies

Learn what 2Is has accomplished for others, and what we can do for you.

Stochastic Modeling


Making accurate bids in order to win business development pursuits.


2Is forecasts accurate prices backed by data that helps customers attain business development pursuits.

Case Study

2Is Inc.’s initial engagement with one of four business sectors of a prime OEM required us to develop a stochastic model for a multi-$B business development pursuit. In one of the final program review meetings with Executive Management, the discussion focused on their internal “Price to Win” Cost when placed on 2Is’ stochastic model “Cost to Perform” S-curve.

The customer’s internal “Price to Win” forecast was less than 2Is’ forecasted “Cost to Perform.” In addition, we were able to answer executive questions by providing answers grounded in the data. The internal “Price to Win” team eventually fell back on assumptions. The Sector President approved a price higher than the internal “Price to Win” team’s recommendation. Our client lost the bid.

One year later, the winning contractor was in default of contract performance requirements, paying significant penalty costs and losing money. The OEM Sector President hired 2Is to model four additional pursuits and priced consistent with the stochastic model S-curve performance probabilities.

Our new customer won all four pursuits, and extended their engagement with 2Is beyond the Stochastic Model into 2Is Inc. Analytic Platform (2AP) to support execution. They are now performing at a level that satisfies both the customer and the comptroller.

Stochastic Modeling graphic

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Multi-Echelon Inventory Optimization


Balance customer availability while minimizing inventory investment and holding costs.


2Is reduces inventory investment costs through the use of stochastic modeling and machine learning capabilities.

Case Study

One of 2Is Inc.'s long-term customers contracted us to support a US Partner-country Performance Based Logistics pursuit of a small, non-US, fleet of aircraft. The operating environment involved a multi-echelon, hub and spoke supply chain to support operations and repair involving multiple levels of component indenture. The challenge is to balance customer availability while minimizing inventory investment and holding costs.

Their in-country supply chain organization, using deterministic models with fixed parameters and rules of thumb, recommended a relatively large inventory investment to support the contractually required operational availability targets.

2Is' approach used a combination of stochastic models and the judicious use of machine learning capabilities. 2Is' inventory optimization approach reduced our customer's inventory investment by 30%, contributing to their winning bid. In the execution phase, the ongoing inventory optimization continues to support Operational Availability targets at a reduced cost. We are now partnering with this customer on a second opportunity with the same Ministry of Defense.

Multi-Echelon Inventory Optimization graphic

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