Retailers are well aware that data is important to their business. The tectonic shifts in retail, from online to real-time omnichannel, from shopping to experience and from West to East all require mastery of data to unlock success.
Data is essential to understand today’s hyper-connected customers and deliver intelligent supply chains that can serve them. The problem today’s retailers face is an abundance of data scattered across their organisations. It’s estimated that a retailer like Walmart collects information on about 1 million transactions creating 2.5 terabytes of data every hour. Cloud-based data, collected from sensors, smartwatches, smart speakers and other wearables connected to the Internet will amount to 35 zettabytes in 2020, according to research from Texas A&M University. Add to that the data collected from social media posts and reviews as well as a host of emerging technologies from robots to VR experiences and the ‘firehose’ of data pumping into retail is extraordinary. But it is all owned by different departments, stored in different ways and used for specific tasks.
Treat data as a true asset
It’s not only the scale that’s the issue but the diversity. Plus, data often has a very limited shelf-life. Retailers are sitting on a wealth of data; the issue is that whilst many pay lip-service to the concept of data as an asset, in reality, they can’t measure this asset, nor can they leverage it for maximum returns. Often it is seen, and treated, more as a liability that is complex and expensive to store, refine and use.
The way forward is as much about having a strategic, organisation-wide approach to data as it is about technology. Fragmented approaches and function- or department-centric solutions may deliver short-term answers for specific questions but will create bigger issues in the medium and long-term.
Allowing operational departments to own data analysis focused on specific business requirements will lead to hundreds if not thousands of siloed analytics projects. Each will be driven by budgetary constraints to look for low-cost options, rather than a strategic data platform that can be reused across departments and for many different analyses. This quickly drives managers to optimise for transactional demands that focus on the liability side of the ledger rather than calculating the overall ROI that could be generated from data as an asset.
This tactical focus wastes time, resource and budget, and misses the real opportunities addressable through integrating data into a unified, usable enterprise-wide resource. We estimate that in a typical data project up to 90% of project time and resource is spent on finding, cleaning and organising data, and only 10% on actually building models and algorithms that can help the business. Repeating this every time the business needs insight is insane.
For data to drive the business needs to truly treat it as an asset and to value the return from successfully leveraging it. This means simplification, consolidation and consistency of all data sources across the business. A strategic, platform approach to data analysis will maximise value and opportunity. But who should lead this work?
Leveraging assets – it’s the CEO’s role
Historically it has often fallen to the IT department. But they are focused on managing budgets – not assets. For them, data is the mechanics of storing, processing and moving bits and bytes. It is important, but they lack the strategic view. Data analysts, whether they are in sales, marketing, procurement or operations understand how to use data to answer questions – but their job is to solve near-term problems, and they too lack the long-term strategic horizon to look beyond immediate uses of data.
Only senior management: heads of strategy, CEOs and CFOs have the overview, authority and importantly mindset to truly define and use data as an asset which can deliver long term competitive advantage. They do not need to be data scientists, but to lead the data-driven organisations that will be the success stories the future, they must champion organisation-wide data platforms. They need to understand how much data the organisation has and where it is. And only by connecting disparate silos together and building the capability to run millions of queries across the business every day will they prosper in the fast-emerging new world of retail.