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According to McKinsey, Retailers who embrace the "Big Data" opportunity could increase margins by 60%. SAP HANA is a key enabler for doing this.


This blog is a collection of questions about SAP HANA usage in Retail that I hear being frequently asked - questions about what it is (and what it's not), how it can be used for real benefit, and what makes it different. It is written with a specific audience in mind - IT people who work in the Retail sector that need to try and explain this "SAP HANA" thing to some of their non-techie colleagues!

For IT people who want more, there is an excellent general SAP HANA FAQ blog that deals with the technical know-how by John Appleby.


1) What is SAP HANA?

  • In very simple terms, SAP HANA is a combination of hardware and software that, together, makes an in memory database that is capable of processing large amounts of data, really quickly.
  • It is an incredibly important new innovation from SAP that fundamentally changes the way that information is stored and reported on
  • It is also one of the hottest new products from SAP in their customers' eyes, with sales of the product exceeding expectations since launch

See Experience SAP HANA for more information.


2) Why is it important to Retail?

  • According to McKinsey, Retailers stand to increase margins by 60% if they get "big data" right. See Big data: The next frontier for innovation, competition, and productivity
  • According to IDC, the world as a whole has generated 2.7 zB of data so far - half of that in the last year alone. As a consumer-driven sector, Retail either generates or would benefit from, a huge amount of that data.
  • It sounds obvious, but data alone is no use. It's the insights that data inspires that are important, and the ability to turn them into action. The "actionable insights" that various strategy consultancies are fond of talking about. SAP HANA means that organisations can take decisions based on larger (and more detailed) sets of data than before. But for SAP HANA, the sheer volume it can handle is not the differentiator to its competitors - it's the speed of processing. Depending on the competitor product, this can be 10x to 100x faster.
  • The time taken from an event happening, through to the action that it prompts can be important, depending on the scenario. If you're a shopper, trailing your irritable child around a store, and having to decide what cereal to buy while you're in front of a shelf, there's no point having an offer presented once you're past that aisle and queuing to pay. For the offer to be relevant, it needs to be in front of you right there, right then. In big numbers, surrounded in a bright colour. SAP HANA provides the capability for tailored offers based on lots of different types of data, to be put right there, right then, based on a customer segment of 1.

3) What are the typical use cases?

  • Promotional analysis. Understand promotional impact and ROI in real time. Enable a pricing strategy that takes into account factors such as stock levels and weather, linked with electronic at-shelf labeling to execute effectively
  • Basket analysis. Analyse POS data to understand the affinity between products within assortments, to drive up sales
  • Profitability analysis. Deep dive into the drivers behind margin development - by category, SKU, store, customer and more
  • Inventory management. Analyse inventory issues at detailed and aggregated levels. Enable stores to learn from each other, and promote best practice by category. Avoid stock outs.
  • Mobile shopper applications. Enable multi-channel shopping and/or protect against "Showrooming". Provide highly-targeted offers to shoppers in real time.
  • Social Media analytics. Analyse social media platforms to understand what sentiment is driving footfall and purchasing decisions, match with relevant data such as sales and inventories, and adapt offers and displays to optimize margins more quickly

Check out the use cases on Experience SAP HANA for more examples.


4) What is "big data"?

"Big data" is a term used to imply an environment where applications need to process larger than normal amounts of information - generally much larger than are typically found in ERP scenarios. The exact size is not specified, and changes as time goes on. Right now "big data" for most people is probably measured in pB, but could sometimes be measured in tB, depending on the industry and application considered. Examples of "big data" could include:

  • Weblogs - information on who's browsing where on your website
  • Social media - What's being said on Twitter, Facebook, other forums, etc.
  • Medical records
  • Geotracking
  • Google
  • Genome decoding
  • Data gather by CERN on its particle physics experiments (http://en.wikipedia.org/wiki/LHC_Computing_Grid)
  • Text transcripts of call centre activities

5) How "big" can SAP HANA go?

SAP HANA can't (currently) manage the kinds of data that are generated by CERN in its big experiments - around 18tB per minute. However, it can manage the kinds of data volumes that are generated in many retail scenarios, such as:

  • Mobile consumer data
  • Promotions and pricing data
  • Stock movements
  • Point of sale data

6) Who's using SAP HANA at the moment?

Lots of organisations globally, including Lenovo, BASF, Cisco, Colgate-Palmolive, Procter and Gamble, Bosch and Siemens


7) What can SAP HANA do that others can't?

The amount of data that SAP HANA can handle gets bigger every month, but the key thing SAP HANA does that is different from its competitors, is to process this data fast. So for any scenarios where timely / real time insights based on a large volume of underlying data are key, SAP HANA presents a compelling proposition.


😎 Is it about steady insight or deal shaping?

Both. SAP HANA can deliver steady insights across a very large stream of events, directing these insights to the relevant person. And it can also bring together large amounts of data quickly to influence a deal or offer in real time - for example in a multi-channel consumer environment.


9) As a retailer, what is the impact of NOT implementing SAP HANA?

Other solutions that handle "big data" are available - and many have been around longer than SAP HANA. Most retailers will have one or more of these solutions in place already. So not going for SAP HANA will enable Retailers to carry on as usual. In this case, the major risk is that competitors will use SAP HANA to their advantage. How much of an advantage depends on the retailer, the maturity of the sector in which it operates, and the maturity of the consumers it serves. For environments where there are a lot of empowered consumers, with a mature online channel, where margins are under a lot of pressure, the advantage could be significant.


10) Is SAP HANA specific enough for Retail?

It's relatively early days yet for SAP HANA, but already there are a number of Retail-specific use cases that make it worth considering seriously. Especially if there's a real need for "Big Data" combined with fast processing


11) How can SAP HANA help increase margins?

All of the applications mentioned above can help increase margins - by as much as 60% if you believe McKinsey. Which prize to go for first depends on maturity. For all Retailers, rapid inventory analysis to manage stock levels more closely will have a business case, as will basket / affinity analysis. For retailers in the more developed markets, applications targeting mobile consumers with offers in real time will have a business case that may be more difficult in less developed markets.

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