So Near and Yet So Far—the Data Centricity Challenge

Interested in Becoming a Member?

An SIM Membership like no other, provides you with an abundance of tools, resources and opportunities to help you achieve your professional and personal success at every step of the way! Be part of our learning community of more than 34,000 corporate and individual members.


For more information about membership, please click here »

Member Login

If u are a subscriber, please use ur subscriber login.
If you are a SIM Member, please use your SIM Membership login.



Forgot your password?

Member Login



Forgot your password?
login  Cancel

Sign Up

If you wish to sign up for a SIM Membership, please click here

Subscribe

If you wish to subscribe to Today's Manager, please click here

If you wish to subscribe to Singapore Management Review, please click here

Website maintenance notice: Website will not be accessible from 27 June (11 pm) to 28 June (9 am) due to scheduled maintenance. We apologise for any inconvenience caused.

Home > Articles > So Near and Yet So Far—the Data Centricity Challenge

 So Near and Yet So Far—the Data Centricity Challenge

by Ian Shepherd | Today's Manager
June 1, 2021
Ian Shepherd, author of The Average is Always Wrong, on how difficult shifting your business towards data-centricity can be.

You’ve hired some data scientists. You’ve allo­cated capital to technology projects with titles like ‘single view of the customer’ and ‘desktop analytics’. You may even have launched whole new ventures like loyalty schemes or product subscriptions on the promise that they would deliver lots of rich cus­tomer data into your business. 

On the back of all that activity, you’ve reviewed board packs that conjure with phrases like ‘big data’, ‘ma­chine learning’, and other buzzwords.

And yet, somewhere in the back of your mind is the nag­ging feeling that none of that has really moved the profit line appreciably northwards. What are you doing wrong?

If that’s you, take some small comfort from the fact that you are in good company. CEOs of businesses large and small, public and PE owned and across a range of sectors have all reported the same gnawing worry. But if it isn’t hiring technical people or funding these new projects which helps businesses turn data into profit, what is it?

C
omparing those businesses which are data-driven to the core with those for whom data science remains an uncomfortable bolt-on reveals three key success (or fail­ure) factors above and beyond the willingness to invest:

 

Management familiarity with what data can do. It’s easier if you are an online startup and have a leader­ship team populated with ex-consultants and bankers who live and breathe numbers. But senior leaders in retail and hospitality businesses, for example, have often succeeded in becoming senior based on their knowledge of customer needs, ability to strike strong supplier agreements, and their operational and organi­sational skills. They may not, however, have had to ex­tract value from large amounts of consumer data—and the skills and even the terminology of data science can be scary and off-putting for them.

Denial.
A natural consequence of that lack of familiarity with data is a kind of corporate denial. That can take a number of forms, ranging from straightforward “not invented here” through to the more subtle denial symp­tom of outsourcing. If we get some clever consultants in to ‘do the data stuff’ we can carry on running the ‘proper’ business uninterrupted, after all.


Fear of failure.
The very essence of extracting value from data is asking a lot of questions about what it is telling you. Setting up hypotheses, building models based on them, and testing those models against con­trol groups is the core process of data science. If yours, however, is a business where executives are rewarded only for association with successful programmes and not for testing things and proving that they don’t work, then the broad and curious approach to innovation which characterises really data-centric businesses is unlikely to flourish.

Those businesses which have succeeded in truly putting customer data at the centre of their operating models are characterised, then, by a broad management team familiarity with the topic of data, including ongoing in­vestment in continued learning on the subject.

They are leadership teams which are constantly asking questions about their business and challenging their specialist analysts to answer those questions. Why do people buy this product more than that one? What could our data tell us about which products to have in which stores? Can we predict complaints and customer dissatisfaction before they happen?

And finally, they are businesses where every key pro­cess, from recruitment through capital allocation and beyond are organised to encourage experiments, to generate yet more insight from data and drive further commercial success.

Getting your business to that point is a culture and val­ues transformation as much as a technology one. It will require open, honest introspection amongst the current leadership team and a courageous willingness on the part of senior colleagues to admit what they don’t know and engage on a learning journey together.

But if there is one thing any analysis of the value of data for modern businesses will reveal—it is that the journey is worth it.




Ian Shepherd is a CEO and CMO who has held senior roles in a range of world-class consumer brands over the last 25 years in­cluding Sky, Vodafone, Game, and Odeon. Ian has launched loyalty programmes, built new digital reve­nue streams for traditional retailers, and turned declining market share into stellar growth—all based on a keen practical understanding of the consumer and of the power of data and customer insight.

Get your copy of Mr Shepherd’s book The Average is Always Wrong.



 IMAGE: SHUTTERSTOCK
Copyright © 2021 Singapore Institute of Management

Article Found In

Today's Manager Issue 2, 2021

View Issue
 

Browse Articles

By Topic
By Industry
By Geography