The impact of digital on the retail sector hit home at the end of May when M&S announced that it was accelerating its digital transformation following plunging profits. That one of the UK’s best-known retail brands had clearly failed to keep up with digital consumer trends may have come as a shock to many. I wasn’t surprised, however. I’ve recently written a paper on this very topic. In ‘Why data is the new retail battleground’
I look at one of the key reasons why traditional retailers are struggling to compete with their digital competitors – data.
For me, the challenge is not that these retailers have failed to invest in online commerce channels. Indeed, many are doing well in this respect. What’s holding them back is that they’re still using decades-old back office systems and processes governing Product Lifecycle Management (PLM), Product Information (PIM) and Product Master Data Management (MDM). These retailers, and especially those with a catalogue heritage, retain a large legacy of systems, processes and cultural norms that are not aligned to the expectations of today’s customer. They’ve typically expanded into digital channels to meet the consumer appetite, but they’re being hindered by operating models that remain wedded in their legacy data management principles.
The Amazon effect
To compete with the likes of Amazon and other digital retailers, traditional companies must transform – and they need to do this fast. The ability to capture the right product information quickly and accurately, then push it out to the relevant operational (Finance, Warehouse, Transport, Order Management, etc.) and commercial (Merchandising, Marketing, Pricing, etc.) systems will be critical for this. However, these processes are typically not well managed, or even automated, by many traditional retailer organisations today. Everything from data input, data cleansing and data matching, data enrichment and data profiling, through to data syndication and data analytics, is still dependent on disconnected and largely manual operations.
It’s clearly time to automate those areas of data management that are tying up valuable human resources in manual repetitive tasks. Trying to do what they do now without automation will not work for traditional retailers. In my paper, I describe a set of automation best practice that all retailers should be considering in this respect.
A strategic choice
I also point out that this isn’t just an IT challenge. It is a strategic choice to build a single source of data truth on which product decisions can be made. This is built on an understanding that to remain competitive with responsive and agile operations, every day, organisations need to bring about both technology and cultural change.
Like many traditional retailers, M&S clearly has a number of digital challenges to confront, such as those described above. After announcing its 62% drop in pre-tax profits, the retailer declared it would be modernising its business through ‘accelerated change’ to cater for an increasingly online customer base. I hope it puts data at the heart of this transformation.
Read my paper for more on how to move to a new data-led operating model in today’s fast-moving retail environment.
Authored by Gary Ellwood