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Monday 14 October 2019

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Data overload

Written by Glynn Davis
15/11/12

There is no escaping the term Big Data, which describes the scenario whereby retailers utilise information derived from multiple sources – both from inside their businesses and from external third-parties.

The objective is to combine the various data inputs and analyse this new entity with a view to it throwing up insights that can then be acted upon to enhance the operation of the business. It is fair to say that this is much easier said than done.

One key element within this process is the use of Business Intelligence (BI) tools that aim to make sense, through analytics, of the growing data mountain. Such tools have been around for some time but with the growth in the number of data inputs – including social media and geo-location information – they will have an increasingly important role to play for retailers in the future.

This is certainly the view of Michael Ross, director at eCommera, who believes an analytics-driven approach is the way to succeed in commerce in the digital age and that understanding how to optimise business performance in this environment is an imperative.

Such is the growing importance of BI that eCommera has been busy building a new methodology for the retail sector, whereby the emphasis is placed on taking actions based on data insight. The idea is that this approach will enable companies to capture, organise and view their data, with a holistic perspective, and from this the technology will recommend optimal trading decisions, dependent on their impact on
trading profits.

This all sounds well and good but the utilisation of BI tools to provide actionable insights from retailers’ quickly growing piles of data is not without its challenges.

Analysis paralysis
Robin Coles, director of supply chain consulting at BT Expedite, suggests: “There still seems to be an analysis paralysis within the industry. Proper time and money should be spent on planning how to use the data – in terms of collection, analysis and findings – so when put into practice it will reap rewards for retailers. They need to be focused on what they want to get out of Big Data, otherwise they could spend too much time and money analysing it, for little or no benefit.”

Avin Wong, founder and managing director at Whichsocial, believes there is still too little understanding of how to collect, manage and analyse the data and that a starting point would be to “define clear business objectives” around these individual areas and that an “analytical mind-set is required by retailers. But to date many merchants have taken a more marketing-led approach to analysing data, with the objective of using it to promote their business to customers – think loyalty programmes.

“Marketers might be creative but when it comes to number crunching they are not naturals. It’s not their instinct. The future job market [in this area] might be more about employing data scientists,” suggests Wong.

Dharmash Mistry, partner at Balderton Capital, agrees: “Start-ups have used Big Data well. You need algorithms and a whole new breed of scientist involved. It’s an investment in high capability individuals and I’m not sure retailers have made the investment. But it’s a big opportunity as great analysis will be a competitive advantage.”

Thankfully the technology exists to help retailers on this path, according to Peter Walker, UK and Ireland country manager at Information Builders, who says: “The technology is available today to consume all data types and to present it to the BI applications and portals that can then ‘push’ it out to all relevant parties [in an organisation].”

He admits there is still an implementation challenge – centring on the difficulty of dealing with so many data sources from both inside and outside the organisation – that makes it tough to ensure there is a single version of the truth that can be used throughout the business.

When added to the growing desire for access to data in real-time and on mobile devices then the complexity begins to mount. But again Walker says there are IT vendors in the marketplace that can help. In this case it is around the management of huge amounts of data – that can be handled either on-premise or hosted externally.

Mobile data
This data can then be optimised and distributed to the users [within the retailer] by the likes of Information Builders. Walker says optimisation includes guaranteeing the integrity of data – that can become an issue when it is derived from so many sources including social media platforms Twitter and Facebook and also from outsourced call centres.

More of a challenge is the growing desire for the BI from the data to be distributed to a variety of devices including mobile phones and tablets, which brings in the issue of scaleability. Nick Barth, retail solutions director at MicroStrategy, suggests BI was originally a desktop product, with scale only becoming an issue as retailers have begun to look into its use on a growing number of mobile devices.

MicroStrategy has developed its BI platform for use on such technology and can now provide its regular rich functionality on the likes of iPhones and iPads, which Barth says has created a “huge increase in the population of users”.

Although the company creates tailored dashboards for individuals such as CFOs and board members it is within stores that he says the greatest interest is now being shown. Carphone Warehouse has certainly found BI useful in its stores network. Paul Scullion, its head of BI development, says: “As it is used by branch managers it needed to provide them with easy to understand insight on store performance. And branch feedback has been unanimously positive.”

This distribution of BI to a wide user base such as store managers has been made easier by MicroStrategy not moving data around – including from the retailer’s data warehouse.

“A lot of technologies cannot deal with concurrent usage. We don’t move the [retailers’] data whereas most BI tools have their own data stack. They take the data from the source and put it into the BI stack and then service users from there,” explains Barth.

This capability has led Tesco to trial the IT firm’s iPhone solution with 400-500 users across its store network. MicroStrategy is also working with Tesco’s Clubcard analysis division Dunnhumby to replace its existing ‘The Shop’ platform for an off-the-shelf alternative that will be used to deliver shopper insight to Tesco’s suppliers.

Such solutions are enabling retailers’ employees – from head office to the shopfloor – to more easily analyse the broad array of data that their organisations are now collecting. The analytical capabilities of these solutions are also improving, which might allay some of the fears of Wong and Mistry.

Walker suggests: “BI is extending into deep analytics. Retailers do not have to employ 100 statisticians to analyse their pricing anymore as BI is enabling forecasting to come to the fore. We’ve embedded predictive analysis in our standard GUI (Graphical User Interface).”

However, there is lots of work still to be done as highlighted by Wong who says retailers have limited knowledge about the newer data inputs such as those from social media platforms. They are also unsure about how they need to be integrated into their other data sets in order that they can play a meaningful part in the way BI is utilised by merchants in the future.

This suggests that Big Data offers a vast array of opportunities but an equally large number of challenges – but at least retailers are making progress with getting to grips with scaling their growing data mountains.


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