Rethinking the operating model: Data as a strategic enabler for growth

BrandPost By Anurag Bhatia, Senior Vice President and Head of Europe at Mphasis
May 06, 2021
IT Strategy

Now and beyond the Covid-19 crisis, companies must transform business models and prioritise data as a strategic enabler of growth.

Anurag Bhatia
Credit: Mphasis

In an economy turned upside down by the pandemic crisis, organisations are seeking any opportunity for growth. The way ahead lies in rethinking their operating models to make strategic use of a golden opportunity already in their hands – data.

Surprisingly, 68% of data available to companies remains unused. Imagine the potential for business transformation residing in unstructured, hidden or unused data. Covid-19 precipitated a jump of around five years in digital adoption in just a few months, opening up access for businesses to the necessary technology to tap into these data sets. As McKinsey has predicted, post-Covid economic recovery will be digitally-led and largely reliant on the optimum use of data.

I’d go a step further and say that recovery will be insight-led, as the pandemic has forced businesses to pay more attention to their data.


Spotlight on data insights

Successful business or digital transformation must be underpinned by clarity on where data is sitting, and how it’s going to be used to serve business goals. Data is also central to transitioning to a remote working model, as Covid-19 pushed companies that weren’t used to supporting a remote workforce to put suitable infrastructure in place to enable continuity.

Gartner outlines that three of the top growth drivers for businesses are increased remote work, use of digital channels and higher need for automation. Coupled with AI and ML, data can facilitate the automation of complex tasks remotely to build an agile, intelligent model that allows continuous innovation. This is where data management and analytics has evolved into DataOps – optimised data management that’s dependent on seamless system collaboration.

Many legacy firms are not prepared to implement DataOps due to the issue of fragmented, inaccessible data that was static or not integrated between internal and trusted external sources. As they start to break down siloes and make this data converge in the Cloud, businesses can reach valuable insights and provide advice or services in real time, thereby monetising their data.


The operating model – old vs new

Typically, companies looked at modernisation through the lens of whether their tech was fit for purpose. The new model has matured towards experience-led product journeys, which means ensuring that product development is closely linked to what the customer wants.

The strategy is to visualise what the end user experience will look like, which informs how to use data for the specific insights to get there, and then build the back end to support it. Not only the pandemic – but digital natives, too – showed how data, and its applicability to how firms connect with their audiences, is the strategic enabler to pivot, expand, and edge out the competition.

We can look at TransferWise as a solid example; the company has far outshone its peers in the Covid-19 fallout, doubling profits in the past year. That’s down to its innovative use of data analytics to drive customer referrals, bringing in around 50% more new users.


AI + data = strategic enabler

If we now look to the insurance sector, providers have been managing an influx of activity brought about by the pandemic, with some firms experiencing a 200% rise in call volumes. This unprecedented surge means they have had to tap into data and resources that were not getting used in the past.

Some big names were primed before the pandemic, such as Aviva’s ADA, an algorithmic decision agent built to cater to an individual’s need at any given moment. Here, Aviva turned its customer marketing strategy from business-facing to customer-centric, and data played the central role. ADA uses machine learning to analyse the historical data held by Aviva to predict what customers may want in the future and their ‘next best action’.

AI and data in tandem can lead to operational and cost efficiency and strengthened customer retention through hyper-personalised services that are more closely aligned with individual needs.


The volume of data produced in the world is multiplying fast, from 33ZB in 2018 to a projected 175ZB by 2025. I see businesses becoming more organised with their data within the next year and, within three to five years, there’ll be real acceleration taking place, after they adopt insight-based models to unlock previously concealed opportunities.

It’s possible to kick off long-term value creation even in the midst of economic uncertainty, and putting data front and centre is the way for businesses to expedite meeting their growth objectives.