With shoppers looking for value and commodity costs volatile, margins are under pressure, meaning pricing decisions have never been more important. Manufacturers and retailers are looking for technologies to help them optimise prices and suppliers of that technology are in demand – as shown by IBM’s deal to buy US analytics firm DemandTec. Glynn Davis reports.
Where to pitch prices is one of the key decisions in the world of retail, but it is also very complicated, which is leading retailers and manufacturers to explore the world of price optimisation technologies. This brings scientific analytical rigour to what has long been an artistic gut-feel endeavour for most businesses in the food sector.
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A desire to play a part in this trend was behind the agreement struck in December by IBM to buy US-based analytics firm DemandTec for US$440m. It is the latest acquisition by IBM as it seeks to strengthen its business analytics and optimisation capabilities, which are a key plank of its growth strategy.
Yuchun Lee, vice president and general manager of the enterprise marketing management division at IBM – into which DemandTec will fit – says it forms part of the group’s “smarter commerce” suite of solutions. “We are helping our customers put their customers at the centre of buying, marketing, servicing, and selling, and price optimisation is a key component,” Lee says.
With margins being squeezed, the increasingly rapid introduction of new products into stores and the tough economy, food companies are recognising the need to apply technology intelligence to their pricing decisions. But what do they get from price optimisation solutions such as DemandTec?
Fundamentally, they get the ability to potentially undertake millions of pricing calculations concurrently, involving three areas of analytics – demand modelling, forecasting and optimisation.
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By GlobalDataDemand modelling rolls together the rules for a company’s pricing strategy (whether it is a value or premium operator), tactical rules (how many promotions can be run at once etc), and the pricing elasticity of individual products.
The latter relates to the forecasting analytics component of price optimisation solutions. All three elements then feed into the optimisation analytics element. Greg Girard, programme director at IDC Retail Insights, says this boils down to the “strategy and tactical rules constraining the answers that the algorithms can deliver, which takes into account cannibalisation and other factors”.
This is typically referred to as ‘what if planning’, where, for a set of goals and a series of inputs, the modelling provides various outputs of suggested pricing strategies, as well as sales forecasts by product within a store or region.
There are many additional insights relating to product affinities sales patterns that become visible during the analytics process and these can be deployed to help assortment, range planning and replenishment. Retailers can then more accurately anticipate and respond to the demand changes resulting from the deployment of ‘optimal’ prices.
Marc Dietz, vice president of marketing at DemandTec, says: “It is bringing analytics to bear and enabling companies to be more competitive through a better mix of prices – both lower and in some cases higher – which can drive margin, and increase market share and improve customer loyalty.”
He claims the accuracy level of Demand Tec’s sales volumes forecasts at specific price points is 90-95%. Against this backdrop, Girard suggests retailers applying price optimisation tools can achieve 5-10% increases in revenues as well as enjoying 3-5 percentage points of margin improvement. “It’s well worth doing. If you do it right then you can achieve these results,” he says.
DemandTec is among a number of price optimisation solutions in the marketplace including SAP‘s demand management tool (formerly KHI Metrics before its purchase in 2005), KSS Retail, which was bought by Dunnhumby in 2010 and the biggest analytics and optimisation firm, SAS.
According to Dietz, DemandTec has the unique aspect of including an assortment solution within its suite, which means it can consider whether a concern with a company’s pricing strategy is a result of an assortment problem rather than a pricing issue.
In-line with the competition, DemandTec is extending its capabilities by using the data inputs it processes (predominantly point-of-sale feeds) to provide shopper insights to its clients. Manufacturers in particular crave greater knowledge of the consumers who buy their products.
Stephen Henly, retail merchandise planning/assortment, promotion and price solutions for the EMEA region at SAP, says: “It enables the manufacturer to realise more gains on their trade promotional spend which can be a large portion of the manufacturers cost of doing business with their retail customers. It helps the retailer and manufacturer to be more fact-based in their decisions rather than just relying on instincts or past processes.”
Among DemandTec’s manufacturing clients are General Mills, ConAgra Foods, Kraft Foods and, more recently Unilever, which it signed up in December to help the food maker understand consumer demand and increase its levels of collaboration with its retail partners.
Daniel Shaffer, director of North American business systems and capabilities at Unilever, says: “DemandTec’s customer trade planning app will arm our field sales organisation with a powerful capability to make the most of our trade promotion investment.”
Lee regards food manufacturers as a “prime Target” for IBM since only 20-25% of DemandTec’s current revenues are from such businesses, with the rest derived from retailers including Target and Wal-Mart Stores.
Also appealing to IBM is the cloud-based nature (aka Software-as-a-Service) of the business. IT capacity can be brought on-stream when it is required, which gives customers the flexibility to be able to scale up and scale down their usage of the software. “IBM is making a bet that SaaS is the future. Since price optimisation software is not run every day – it is in spikes – you need elastic computer power,” says Girard.
This is not lost on rival SAP. Henly says: “It certainly provides many advantages such as speed and value. Clients are able to tap into the specialist modelling expertise of the vendor thus reducing the need for specialist skills in their organisations.”
Being cloud-based also ensures that there are relatively low start-up costs to implementing the solution, according to Lee, who says “the payback can be within the year” for customers. “As it’s not ‘bleeding edge’ technology we are looking to bring it to the masses. Delivering the right price is everything and when you combine this with IBM’s global reach then the solution is a winner.”
