Supporting M&A with Operational Optimization — Part II
By: Opex Analytics
Tags: Operations, Optimization, Logistics, Business Strategy, Supply Chain

Supporting M&A with Operational Optimization — Part II

Welcome Back

In our first series of this blog, we talked about the wave of M&A activity and shared 7 examples of how strategic optimization should be explored to support this activity. We also talked about the elusive “size of the prize” as companies go after big value targets, but struggle to truly operationalize and achieve these synergies. In this blog post, we share examples of how operational optimization should be explored to support operationalizing benefits from M&A activity.

Operational Optimization

An operational optimization process looks for cost savings at a tactical level. It requires more frequent analysis as compared to a strategic optimization process. Normally, the output of an operational optimization initiative is customized software that makes automated optimal decisions. Some examples of operational optimization that should be explored in M&A activity are:

Inventory optimization and multi-echelon safety stock calculation. The basic models dealing with inventory optimization are EOQ (Economic Order Quantity) and Newsvendor model. EOQ model finds the optimal batch size or order quantity when demand is deterministic or accurately forecastable. On the other hand, Newsvendor model deals with uncertainty of demand, and finds the optimal order quantity plus optimal safety stock to buffer against this uncertainty. These models can be expanded to address the complexity of inventory management in the supply chain — optimizing inventory in a multi-echelon supply network. At Opex Analytics, we developed a tool to optimally calculate the safety stocks of different stocking locations given demand forecast, BOM and sourcing configuration. This tool uses an inventory optimization engine as its decision making brain and automatically calculates the safety stocks and order quantities. Transportation planning and vehicle routing in optimizing distribution operations and increasing fleet utilization. In theory, transportation optimization and planning problems like TSP and VRP are among the hardest problems to solve. In practice, these problems are also complex. However, recent increases in computing power have helped the transportation optimization. One example would be planning of the optimal multi-stop routes with consolidated loads for trucks to deliver products to customers. This will increase truck utilization and drive more benefit from truck load. Sourcing optimization. Selecting competitive suppliers and maintaining time-based competitiveness is important. Optimization models can be used to determine the optimal number of sources and the ordering lot size. The importance of transportation operations and costs in sourcing decisions highlights the value of aggregated optimization and decision making in supply chain. In addition, Multi-Objective optimization models are good tools for supplier selection based on price, delivery, lead time, quality and risk criteria.

What about Revenue and Pricing Management?

Most supply chain optimization models assume inelastic demands and start optimizing the supply operations accordingly. However, the actions taken on supply chain might change the demand process and an effective pricing optimization in conjunction with network design, transportation and inventory optimization could increase profit. Effective M&A work should include revenue and pricing management coupled with supply chain optimization to maximize profit across the enterprise.

In Summary

We are in another wave of M&A activity and there are no signs of slowing as companies across industries go after the elusive “size of the prize”. Much has been written about the difficulty in truly operationalizing and achieving expected synergies.

If supply chain leaders are brought into these efforts early enough, supply chain optimization efforts can enable the identification of additional synergies not considered, and may challenge some early cost savings assumptions that companies could struggle to operationalize. Supply chain optimization cuts through operational silos that tend to be barriers when savings/synergies are being defined, and can provide better up front feasibility analysis. In this blog series, we have provided examples of both strategic and operational optimization that could aid in going after the “size of the prize” in M&A activity. There is a lot of upside to leveraging supply chain optimization to support M&A activity beyond traditional network design. Companies will serve their stakeholders well by understanding all the potential applications of supply chain optimization to maximize customer satisfaction and enterprise value.

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