Early data discovery
Most of our projects rely heavily on the analysis of your data, and experience shows that an initial, rapid discovery of the data will increase the accuracy of project plan and timing. We therefore typically proceed withan open business discussion, to grasp the pain points,a data extraction, followed by a rapid data discovery analysis.
This will allow us to verify the feasibility of the initial project goals and in some cases result in the discovery of alternative goals, for examples when we identify unexpected 'low hanging fruits'.
We frequently meet our clients in the initial phases of a project. Subsequently most of the work is done remotely. For productivity and security we only operates in our proprietary cloud computing environment.
Areas of expertise
We are specialists for demand forecasting in large retail, wholesale and manufacturing. We know the particular challenges of these industries, and we have developed a strong technology and a set of solutions
that address these problems. Some examples include:
- Slow rotation products/long tail of the product portfolio. A classic problem for eCommerce, retail (particulary on the point of sale) and hardware wholesale is sparse data, i.e. products selling only infrequently. Classic ‘mean’ forecasting theory is unsuited for this type of data, and we have worked extensively on solving the problem. Quantile forecasting is our solution to this challenge. It has been known in statistical research for decades, yet we are the first to recognize its value for inventory optimization.
- Point of sales forecasting for large retail networks. On the point of sale, a high complexity is introduced both by the sheer amount of data and by the sparsity of the data. Today, only very few retailers have sophisticated forecasts in place at this level, even though often more than half of a retailer's inventory is in the stores. We have been fortunate to work with Europe's leading retailers in this domain and developed point-of-sale forecasting technology that is particularly suited for the characteristics of store replenishment.
While working with our clients we have come to realize that forecasting is only part of the challenge, the translation into a smart inventory policy requires analytic tools and processes that optimize the reorder point and order quantities.
Optimizing inventory is ultimately not only an operative but also a financial problem of balancing the cost of overstock with the cost of stock-outs
. Building blocks include reorder points, order quantity and replenishment policy
Working capital optimization
Inventory can tie up a lot of cash. The good news is that the potential for optimization in most businesses is significant. When exploited smartly, this can turn from headache into a strong competitive advantage. Exemplary projects include:
- "Return on Inventory" optimization: Maximizing availability and turnover for a given amount of working capital that can be invested in inventory, or alternatively the release of working capital for a given service level.
- Stocking decision: Especially in the long tail (low rotation products) the decision to stock a product or rely on cross-docking or drop-shipping is a difficult trade-off that requires reliable forecasting of sparse demand in combination with a thorough analyzes of the underlying economics.
We can help you optimize the pricing of product portfolio. Whether it is a full price store, promotional pricing or flash sales. As is the case for all of our software solutions, a thorough analysis of your sales data can provide an incredibly rich outcome in terms of revenue and profitability optimization.
Loyalty card data
Customer loyalty data is incredibly rich on information, and making sense of it is one of the most profitable analysis we have seen. Customer loyalty initiatives, promotions, cross selling, vouchers etc. are only a few initiatives that build on loyalty data.
Grown out of our inventory optimization practice, we have developed a strong expertise in on-shelf availability. Our solution Shelfcheck
has strong performance characteristics, and we have been able to build a lot of know-how in this area.