When you know what you want to achieve, but you need to understand what decisions will be required over the coming years.
Services: Growth Strategy | Decision Analytics
Timescale: 16 weeks
Our client was an established 3rd Party Logistics (3PL) provider, that was in the process of taking on a new UK wide customer.
This customer was looking to increase market share through a significant change in pricing policy and wanted to understand what network should be put in place over the coming years in order to support this growth.
Our first step was to build up an understanding of the current network – what it could handle, what growth capacity each warehouse could handle and a view of the relative efficiency of each site. From this, a view of the realistic options could be built up; given lease breaks, when could sites be exited / which sites were a priority to leave / where were the parts of the country that were under-served.
With the absence of any forecast volume at anything other than the highest level, we built a data pre-processor, to allow potential forecast scenarios to be explored, answering what if questions such as ‘What if all the growth is in this type of customer?’, or ‘What happens if the average cube of product changes by 20%’. This allowed us to focus on priority areas to support the strategy.
Finally, we built a network optimisation model, to look at the cost of serving the customer base through alternate network structures and volume forecasts. With the absence of any certainty on what might happen, it allowed the customer to test a series of scenarios, and build consensus on what ‘must’ be done and what likely next steps were in the light of the impact of pricing changes.
We delivered the insight to get the decision making moving. In the absence of detailed forecasts that the business could sign off, we provided a framework to allow the customer to confidently make the decisions that were required with as much confidence as possible, understanding the trade-offs that they were making, and setting what was required in order to support the business in the coming years.
Translating the impact of business projections on complex operations into actionable insights.
By creating a consolidated dataset, analysis of different hypothesis could be undertaken in minutes, rather than days.
Developing a tool to dynamically manage storage solutions.