Big data will save your ‘slot’ and make shopping greener

13 January 2014

Dr Arne Strauss

A new operational strategy mining big data to predict when online shoppers want their weekly food shop delivered will not only improve service for customers but boost retailers’ profits by four per cent.

Retailers who offer home deliveries are often working on very tight profit margins since the delivery operation is a significant cost driver; especially if the retailer commits to offering tight delivery time windows in an attempt to increase customer satisfaction and to keep failed delivery attempts to a minimum. Accordingly, they are constantly on the look-out for ways to make deliveries more efficient and greener.  

New research by academics from Warwick Business School, Lancaster University Management School and the University of Southampton have devised a new analytic approach that helps retailers to decide when to incentivise customers - by, for example, lowering delivery fees -  in which area and in which time slots all in real time. This will make the future delivery operation more efficient and therefore greener as delivery vans will use less fuel.

The new approach was tested using real shopping data from a major e-grocer in the UK over a period of six months and generated a four per cent increase in profits on average in a simulation study, outperforming traditional delivery pricing policies.

According to the Institute for Grocery Distribution, online shopping sales of food and groceries are set to increase by 126 per cent over the next five years, taking sales up to £14.6 billion. As tablet and smartphone usage becomes more widespread, shopping online has become quicker and easier and the speed of delivery has become critical in the online fulfilment race.

The group of researchers, which includes Arne Strauss, Associate Professor of Operational Research at Warwick Business School, propose an analytic approach that will predict when people want their shopping delivered depending on what delivery prices (or incentives such as discounts or loyalty points) are being quoted for different delivery time slots. It takes into account accepted orders to date as well as orders that are still expected to come in.

Dr Strauss said: “Traditionally online retailers would collect orders including delivery time requests until a certain cut-off time and plan their delivery schedule accordingly. Therefore, maximising profits is a problem because the final set of orders for a given delivery day are not known until shortly beforehand, yet decisions on the pricing of delivery time ‘slots’ have to be made in advance based on an estimate.

“With our new approach we demonstrate that analysing the customer data which is already at retailers’ fingertips and using it to predict the impact of future expected orders in the estimation of delivery costs produces higher profits than only using orders accepted to date in this estimation. 

“Our model can outperform the static two-tier delivery pricing policies that are often found in practice by around four per cent in profit. In an industry that operates on very small margins, this profit potential is significant.”

Dr Strauss believes online retailers are missing a number of tricks to make more money from their delivery service including  combining demand management with vehicle routing optimisation software, and maximising the use of customer information to segment and target customers.

He also recommends that online retailers try and nudge customers into the most profitable delivery times which could result in a significant increase in profits as demonstrated in the study. 

“It is important to incentivise customers and steer them to particular delivery times,” said Dr Strauss. “This could be in the form of ‘points’ or vouchers or even something along the lines of asking the customer to consider the environmental impact.

“If they are not being given incentives when it comes to requesting their delivery times, then this can have a large impact on route planning and efficiency for the delivery team.

“Business failures such as Webvan who went bankrupt in 2001 after trying to offer a same-day delivery service brought home the message that while small delivery windows appeal to customers, they do cost the retailer money.”

Dr Strauss now intends to perform research into the new shift in online grocery shopping, same day delivery.

The full paper Choice Based Management and Vehicle Routing in E-fulfilment is available here.

See this article featured in The Conversation, BusinessGreen and CMO.

D Arne Strauss teaches Text Analytics on the new MSc Business Analytics course and Modelling & Analysis for Management on the Warwick Executive MBA.

The new MSc Business Analytics course will start in October 2014 and will enable students to analyse large data sets to gain insights which can be applied to real life business problems.

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