Hubris is an ugly trait.  Self-congratulation smacks of arrogance yet there are times when one simply has to say things as they truly are.  In this case:

There.  Told you so.

This article written for the BBC encompasses so many of the aspects of technological disruption within the Retail & Hospitality sector that I have been banging on about over recent months.  AI, Supply Chain forecasting, Loyalty, customer hyper-personalisation, PoS Card Linking, intra-day dynamic pricing - they're all in there.  Since parting ways with Hitachi I have sought to continue my articulation of the contemporary themes impacting the verticals as the Covid-19 pandemic further massively complicates how businesses grapple with coming to terms with Digital Transformation.  Somewhat late to the party but nonetheless welcome (last orders are about to be called but do help yourself to some peanuts), the BBC piece seeks to collate multiple technical trends and at the same time, inject an open-ended question relating to the societal impact of the burgeoning exploitation of personal data.  

Data.  At its heart, as I continue to say, Digital Transformation is about putting the customer at the centre of business-focused reasons to transmute and to do so requires both data themselves and the means to explore, understand and exploit them.  The sensors, devices and application (Apps) designed to harvest and create data only add to the truism that I have continually witnessed first-hand for years, namely that Retailers have, and have had, more than enough data than they can deal with for decades.  'New' technologies simply add to the burden of sifting through volumes of the stuff in an attempt to determine if there are underlying trends, patterns and nuances that had previously been undetected.  Those organisations which get it right create subsequent Data Monitisation capabilities where the imperative of a clearly articulated and executed Data Strategy becomes crucial - but what are the main components of such a strategy?

In simple terms a Data strategy is a vision for how a company collects, stores, manages, shares and uses data.  The MIT CISR Data Board website in the previous link (above) provides the following data strategy definition as: 

“A central, integrated concept that articulates how data will enable and inspire business strategy.”  

In other words, a company’s data strategy sets the foundation for everything it does related to data.  There are many reasons as to why this is important, however I would argue that the four most crucial benefits are as follows:

1. Unlock the Power of Data.
Is the value of your data well-understood in the business?  Once collected, Data must be converted into a useful form, sharing it across the organisation and deriving insights from it.  A Data strategy gives employees guidance on how to do these things and helps ensure people across the organisation do so in a consistent manner.

2. Handle increasing volumes of Data.
It's a sobering statistic that c.90% of the data in the world today became available in the last two years.  As the volume of Data increases, managing it becomes more challenging and the need for a Data strategy grows.  Retailers need to put a Data strategy in place because relying upon an informal approach in today’s data-centric world will likely lead to inefficient Data usage, lost Data and incorrect insight into customer behaviour.

3. A Data Strategy Improves Data Management across the entire organisation.
Data access and usage must be seen as organisation-wide needs as they affect every group, department and seniority level within a company.  That’s why it’s critical to implement a Data strategy company-wide.  Doing so improves Data management across the whole organisation and ensures various departments work in alignment with each other, rather than against each other - and for the good of the customer at large.

4. Data Strategy helps to use resources efficiently.
Not having a Data strategy means that different departments and individuals will solve Data issues in their own.  This risks the creation and/or proliferation of Data silos in addition to a much wasted resource, time and energy.  With a Data Management Strategy, every department and individual will have guidelines to follow related to what format Data should be in and, critically, how it should be used.  This ensures that consistent KPIs and company-wide metrics can be measured to track how the customer responds to initiatives.

Hopefully the benefits are clear for all to see.  Data is so important in today's transactional world that to not employ and execute a Data Strategy is little short of corporate suicide.  Rather than further propagate the hubris of forming another of my own conclusions I will instead leave the last words once again to MIT - even though they are words I could have quite happily have written myself...

"A data-driven company pervasively creates, integrates, and liberates analytics knowledge to help people and processes continuously work smarter.  Becoming data-driven requires much more than hiring data scientists and rolling out dashboards and visualisation tools; it requires building an enterprise capability that can regularly generate innovative new analytics-based work practices and scale best practices across the company.  Companies with a data-driven capability are more likely to maximise returns from data—and to produce unique knowledge that creates competitive advantage."