Decoding the transformation conundrum

Digital transformation has been on the agenda for organizations for the past decade and a half. Since the pandemic, however, the adoption of technologies such as advanced analytics and AI has surged amongst enterprises of all sizes, leading to certain roadblocks during their digital transformation journeys. And, amidst this uncertainty exacerbated by the viral outbreak, business leaders are increasingly taking decisions that will alter their company’s growth trajectory for years to come.

Data and analytics have emerged as an essential component for modern enterprises to seamlessly navigate the uncharted waters where tides continue to shift. In a recent ET Live Roundtable, Data Sessions powered by Qlik, local business leaders talked about how they used data to minimize challenges and maximize business value during the pandemic – and how they see it driving innovation in the future.

The transformative power of technology

Throughout history, technology has served to optimize “work”, be it something as simple as operating lifts or switchboards, or doing high-precision electronic manufacturing. The extent of the current tech-led disruption is such that we do not even recognize some of the low-skilled tasks as jobs anymore. One such example is that of a knocker-upper, someone who used to get paid to wake people up who wanted to get to work on time or didn’t want to miss their morning meetings.

“It used to be a well-paid job until about a hundred years ago in Britain and Ireland,” explained Akhilesh Tuteja, Head of Digital Consulting at KPMG. “Today, it is simply done by our alarm clocks and smartphones. Data and analytics have the potential to similarly displace yet another elite profession – that of astrologers. They have far better predictive prowess than any astrologer when it comes to business outcomes. I have been involved in a number of digital transformation initiatives where technology has enabled decision-making, at speed and scale, something which would have been impossible for a human mind to achieve by itself.”

He further added that data analytics, with its unrivaled predictive and prescriptive ability, has the power to grant three of every CEO’s wishes: “My revenues skyrocket, my costs go down, and I continue to manage risks well.”

However, the potential of AI, analytics, and allied technologies are not limited to just curtailing the expenses. As Alok Khanna, Executive Director from Indian Oil, explained, “Technology can also help us use our assets more effectively, improve production performance, boost the bottom line, or simply enhance the customer’s or the stakeholder’s experience.”

Challenges that companies should be prepared to deal with

Companies of all sizes need to consider a range of factors before they can come up with the right data transformation strategy. These mainly revolve around the three ‘S’s: Scale, Security, and Skill.

“In Indian Oil, whichever system we need to implement, we have to consider the scale before everything else,” Mr. Khanna explained. “When customers were asked to feed their Aadhaar details, many of the local cyber cafes were booked by distributors because there was so much rush. It was almost 25 crore customers who had to feed their details in 80 days or so. This is the scale I’m talking about. I cannot develop a prototype and call it a success unless it is proven to handle a scale such as ours. While implementing any digital solution, it has to be scaled up to 11 refineries.”

Large companies, therefore, need to factor in their size before they embrace the digital transformation. For Indian Oil, for instance, the issue of system availability ties in with the scale. “Indian Oil works 24/7, so the system must be on at all times. Many systems were automated to make customer service available 24/7. We can’t work with the call-center concept.” To illustrate his point, Mr. Khanna shared the story of how Indian Oil registered a sharp decline in the number of complaints being lodged after they installed a chatbot-driven self-service platform which could provide solutions to common issues.

Data analytics, he argues, can also play a major role in improving key operational KPIs, particularly for a company such as Indian Oil that employs a customer-facing system generating real-time data that is analysed through the use of Qlik. “There is ample scope for data analytics in digital transformation projects, value maximization, topline improvement, cost reduction or even predictive maintenance. It can even be extended to aspects such as operational effectiveness or availability improvement. We have seen the benefits in our ML-based analytics projects and some of these projects are now being scaled up to cover ten refineries. I find that such analytics applications have an impressive scope for future adoption.”

However, while building a robust technological infrastructure, businesses today cannot afford to ignore the security aspect. Security – both physical and cybersecurity – has become a critical business imperative, especially in view of the surge in phishing and ransomware attacks on enterprises during the pandemic. A single malfunction or cyberattack can cost a company not only financially but also in terms of depleted brand value.

Finally, the workforce working within the organization undergoing digital transformation must be equipped with the necessary skills to effectively engage and work with the new solutions. “If a technology is made for a particular demographic, such as IT professionals, then won’t become popular. But if it is made for the masses, if I can percolate the knowledge to the lowest-level officer who can do self-service, then we can reap lots of benefits,” Mr. Khanna said.

New world, new skills

Data analytics is no exception to this rule, as he feels that organizations seeking to integrate data analytics into their tech infrastructure must ensure that their employees across all verticals are data literate. This perspective reveals a marked shift from the traditional approach to analytics, in which only a specific set of people used to engage with analytics, churn out data, and present it. Today, new-age professionals are curious and keen to explore new domains. In fact, according to research by Qlik, almost half (45%) of respondents from India feel confident in their data literacy skills (i.e. the ability to read, work with, analyze and argue with data).

The study further showed that employees across India acknowledge the value of data and data literacy in their jobs:

  • 99% agreed that data helps them do their job better
  • 96% think higher data literacy would enhance their credibility in the workplace
  • 93% believe data literacy would increase their value at work

The rise of self-service technology is aligned with this demand. Modern organizations need to inculcate a work culture where each employee across all verticals is equipped to make mission-critical decisions aided by the power of data analytics. For instance, the front line needs to be prepared to take decisions on the field. Enabling them with the right set of tech skills will maximize the potential of analytics. Therefore, the democratization of data and analytics is another key part of a robust data – and, by extension, digital – transformation strategy.

According to Subrata Dey, Global Chief Information Officer at Godrej Consumer Products Ltd, it is essential to empower the workforce with the skills to navigate data on their own by democratizing analytics. “Today, people want to explore what technology can do for them. Analytics cannot be the job of only a handful of people. It must be democratized with the right set of technology and skills to maximise the benefits it delivers to enterprise operations.”

“Data tells, story sells”: How companies can build a strong data analytics pipeline

The purview of data analytics continues to increase in scale as technological progress optimizes its efficiency and effectiveness. “Up until a few years ago, many companies, including ours, began their digital transformation journeys by relying on descriptive analytics. We had data and the tools to generate reports based on that data,” Mr. Dey continued. “Now, you have moved from descriptive to predictive and prescriptive analytics. Today, nobody is interested in doing a postmortem of the past. Important as it is, looking at the past does not tell you the entire story. Companies have now begun to focus on how they can use the data to generate better insights as well as foresights.”

He revealed how Godrej has scaled up its analytics operations from India to international markets, encompassing key areas such as manufacturing, sales, and finance. He also highlighted the evolution of analytics from a reactive function to a predictive and preventative function that can help unlock better opportunities when upsellng, cross-selling, or servicing customers.

While the benefits of analytics are many – and the scope continues to expand – it comes with its own set of challenges. For instance, irrespective of the advancements in this space, it cannot be expected to yield results without an adequate data infrastructure in place. “Data quality is critical. If the quality is not right, it is just garbage in, garbage out,” he added.

Therefore, ensuring master data management and proper ETL tool to extract, transform, and load data, etc. are essential to effectively convert all types of data – be it structured, unstructured, internal, external, social, third-party, etc. – into actionable insights that can be implemented across the board. “The key question is, once you see the opportunities, what is the pace at which you can scale up? Selecting the right technology is important. This applies not only to technologies related to analytics but the entire infrastructure which will be behind it. Otherwise, you will have tons of data but not be able to figure out what to do with it.”

Besides setting up the right technological framework, he argued, companies must also develop the right data strategy to extract the maximum value from their data lakes. In fact, integrating the relevant combination of technologies and processes is a part of the optimal digital transformation strategy. Doing so can help businesses tap into superior levels of efficiency and productivity.

Mr. Tuteja agreed with this sentiment. “At KPMG, we think the power of cloud and analytics coming together will create many things that are considered impossible today,” he said.

Future scoping: What does data analytics’ next stage of evolution look like?

The conversation ended with Mr. Dey and Mr. Tuteja talking about the future of data analytics, especially involving the reduced dependence on data scientists to extract value from data. New-age data analytics companies such as Qlik are already leveraging a combination of data analytics and NLP to enable users to input queries through a voice assistant and receive the output in an audio format or on their smartphone screens. Moving ahead, the marriage of cutting-edge technologies with data analytics may give rise to a model that is capable of providing answers to questions that we haven’t even thought to ask.

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of ET Edge Insights, its management, or its members

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