By Mark Hinds, CEO of Polymatica.
UK retailers are feeling more pressure than ever before due to rising costs and increased competition, as such, they should be doing everything they can to remain competitive.
Many retailers are already aware that data is one of the most valuable assets they hold, however, just having it doesn't necessarily mean it is being learned from. In an ideal world, each part of a retailer's operation should be analysing the vast wealth of data they hold at every level and in every department, to make more intelligent decisions; but the reality is that this simply isn't happening.
One issue is the sheer quantity of data being analysed. As data volumes double every 18-36 months, traditional business intelligence (BI) and analytics solutions are simply failing to keep pace. Analysis is often measured in days, rather than seconds, minutes or hours. Retailers therefore face a stark choice; restricting themselves to narrow subsets of data in order to receive limited insight in a timely fashion, or performing a more in-depth analysis that cannot necessarily give insight at the speed the business needs.
Another issue is who can actually perform the analysis. Most retailers have a large pool of staff with deep expertise in different areas of the business. If these subject matter experts could analyse data directly, they could drive enormous additional value and revenue. So why is this almost never achieved?
Over complicating the issue?
Data analysis has a reputation for being difficult. Most established BI and analytics tools require specialist skills – including in-depth knowledge of mathematical modelling, an understanding of Machine Learning techniques, and coding languages such as R or Python. It's not hard to see why this might be off-putting to someone whose expertise lies in logistics or purchasing.
As a result, most retailers rely on trained data scientists to perform analysis. This presents a bottleneck, increasing the time analysis takes and reducing the organisations' agility. After all, these trained specialists will probably lack detailed knowledge of specific business units – meaning any insight will need to rely on a back-and-forth with business specialists, or risk insights that are incomplete at best, and misguiding at worst.
But how can retailers empower subject matter experts to analyse data directly?
The first and most obvious step in encouraging wider engagement with analytics is to put in place the right tools. Most retailers understand that speed and power is critical to digesting enormous amounts of information in near-real-time, with no pre-filtering. Yet just as important is technology that feels accessible, and that can offer step-by-step support for the non-professional. Any such platform should make the common functions easy – with templates for complex tasks, as well as tutorials, dashboarding, and easy-to-use visual modelling.
Even so, as analytics can seem intimidating to the uninitiated, you'll need to address the employee 'fear factor'. In truth, all that retail users really need to get started is an understanding of spreadsheets and basic maths, and a willingness to give it a try. The trick is in helping them to recognise this, and encouraging them to engage with data.
Retailers should look to identify those individuals who are willing to try using data to their advantage. Investigating who, whether existing staff or a new hire, can bridge the worlds between data and the business is a huge advantage. This person can help employees identify the questions they need to ask to get the insight they need from the data that is available. This won't be an overnight process. Employees need time to recognise the benefits of engaging with data – to the point they start to become internal advocates and spread their message within the organisation.
Retailers will also need to engage with their IT department to ensure that data is not exclusively 'controlled' and ring-fenced. Taking up data scientists' and IT professionals' time to help other employees access data directly should be framed in terms of the clear long-term benefits. Ultimately, it will free up data scientists and IT professionals to do more valuable, skilled tasks – in other words, a win-win.
A new outlook
Making use of real-time data analytics opens up a whole host of new possibilities for retailers – something which could be hugely beneficial during uncertain times. A retailer could, for instance, explore sales data in far more detail as part of a discussion on which lines are selling best to investigate how they can replicate success across other products. Analytics can help to drive far more intelligent decisions being made across the organisation, which will have a bigger long-term impact because they're based on the entirety of a retailers data, not subsets. The potential made possible by these systems is almost endless and could be the magic bullet that help retailers succeed at a time when others aren't.