Digital Goodie Write-up On Picking Profitability
TABLE OF CONTENTS
1. INTRODUCTION
2. COST OF PICKING IN STUDIES
3. DIGITAL GOODIE PICKING EFFICIENCY
4. PROFITABILITY CALCULATIONS
5. CONCLUSIONS
1. Introduction
We are seeing an increased interest in store fulfillment as it ties into several mega trends in the industry such as convenience, lowered delivery costs and green values. For example, Chris Conway – Digital Director at the Co-op UK – has estimated that the Co-op UK will save 40% of delivery costs when utilizing store fulfillment as opposed to a centralized warehouse model.
However, store picking has traditionally been seen as a very expensive process. To tackle this dilemma, Digital Goodie has chosen optimized store fulfillment as one of the key strategic focus areas of the company. Significant profitability gains can be achieved with the deployment of state-of-the-art in-store picking solution. The document will reference both independent studies on the cost of picking, as well as direct profitability calculations using anonymized data from Digital Goodie customer cases.
The calculations provided herein are focused on profitability gains. A more detailed ROI estimation and analysis can be provided on a per retailer basis as it requires cooperation to take into account the unique circumstances of each retailer.
Over the last few years several independent studies have been carried out around the cost of manual store picking. The general finding in all of these is that when providing either click-n-collect or home delivery of groceries, the in-store picking is one of the costliest steps of the fulfillment process.
McKinsey – a well known global management consultancy agency – has published an interesting study called: “Shaping the future of online grocery”. In the study McKinsey found that the cost of picking was ca. 8% for UK supermarket’s online cost base.
Figure 1 McKinsey Shaping the Future of Online Grocery
Figure 2 Credit Suisse report on Online Grocery
Another often quoted study was carried out by Credit Suisse “Report on Online Global Grocery”. Their findings were similar, estimating that the costs of picking for a 90£ basket were 8.54£ corresponding to 9.5% of the basket value. Interestingly the study found that of the total cost of home delivery with store fulfillment, the largest cost component was picking, contributing 33.1% of total costs.
Both of these reports clearly indicate is that grocery retailers should consider optimization of the picking process as a key priority when launching their online operations, due to its significant impact to profitability.
3. Digital Goodie picking efficiency
Digital Goodie has been involved with store fulfillment for the last 8 years, since the launch of our first picking application. This means that we are experts in our field, and we have a great deal of experience in developing the software solutions for both commerce and fulfillment proesses. Our deep engagement with customers has led us to accumulate deep domain experience in working with to optimize their in-store processes. This is evident in the fact that we have been able to increase picking efficiency at key customers by close to 100% from what it was with the first generation of our picking software. This efficiency improvement is also a testament to our commitment to continuous improvement in the field.
Today the most efficient customers’ stores achieve close to 300 items/hour picking efficiency. The benchmark we have used in our profitability calculations is 200 items/hours. This later value is still 33% more efficient than the best reported picking speeds reported by McKinsey.
Figure 3 McKinsey Shaping the Future of Online Grocery
When making the profitability calculations we used data from live installations wherever possible. The example basket used had a value of 80€ and contained 40 items. For cost of labor we used a reference salary of 14€/hour. The key findings are presented in the table below.
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As can be seen, the total savings per pick that can be achieved via the use of Digital Goodie Picking application have been calculated at 6.04 € / pick. Note that the cost of DG assisted picking contains the SaaS fees of the DG solution.
When calculating costs of errors, we only attempted to estimate direct costs to the retailer. The indirect costs incurred by customer dissatisfaction were not estimated in these calculations, such costs would include:
From both Digital Goodie’s decade worth of experience, as well as from all independent research produced in the industry, it is evident that one of the most central processes to optimize in conjunction with store fulfillment is the picking process. The value of an efficient picking solution is very high.
All of this indicates that in-store picking solution is a complex software and should not be seen as stand-alone component. An efficient picking solution is an integral part of the end-to-end process optimization of the online commerce. Retailers can build significant competitive advantage over tight process integration and data analysis, which can be achieved only by deploying solutions supporting aforementioned; hence it is key to choose a partner that focuses on this in the long-term to ensure that the chosen solution will grow and evolve with the needs of the retailer.
References:
McKinsey & Company “Shaping the Future of Online Grocery”
https://prod-wp.pub.coke.com/wp-content/uploads/sites/24/2016/10/CCRRC_EU_Shaping-the-Future-of-Online-Grocery_032015.pdf
Credit Suisse “Report on Online Global Grocery”
https://plus.credit-suisse.com/rpc4/ravDocView?docid=_X0Qw2AN-V1Ni