What to do when your current solution becomes less than optimal.
Sector: Retail & E-commerce
Services: Decision Analytics | Growth Strategy
Timescale: 16 weeks
Automated warehouses can be perfect for a business with a stable operation; where they struggle is when the requirements of the business evolve, and the solution quickly becomes sub-optimal. The challenge in this instance was to build a business case to put a significant volume of business through a new, manual solution and then deliver the operational solution.
There was broad agreement that ‘some part’ of the range should be picked through a manual solution, rather than through the automation. What was required was a deep understanding of the full product range, and how much of that (from a sales velocity and product cube) should form part of the automated solution.
This was analytics, and we came up with a strong answer. Alongside this, we needed to develop a lifecycle management process, so that products could be moved between the manual and automated solution on a weekly basis, ensuring that the ‘right’ products were in the ‘right’ solution each week.
The solution was designed, trialled and delivered as the business moved out of the summer, and was established and in place for the client’s most successful Q4 in a number of 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.