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Why Leveraging Data Meaningfully is the Key to an Organisation’s Success

Why Leveraging Data Meaningfully is the Key to an Organisation’s Success

Even if you are, leveraging the data meaningfully is a different ball game. Getting that part right is key to success in your organisation's digital transformation drive.

Illustration by Raj Verma Illustration by Raj Verma

Kitchenware, a small utensils shop in old Gurugram’s Sadar Bazar, recently digitised its inventory. Every product in the store was barcoded, easing the billing process. But the data wasn’t used to analyse fast-moving and rarely moving products, which could have simplified inventory management—for example, which item to stock more, or which item to reorder at more frequent intervals, among other things.

Now, munch on this. When India went into its first Covid-19 lockdown in March 2020, GCMMF (Amul) was able to successfully deploy a frozen food supply chain to deliver dairy products overnight, R.S. Sodhi, MD of Amul had earlier told Business Today. By maximising the use of data, software and digital infra, Sodhi was able to manage inventory in a way that the retailers never ran out of stock of key essential items.

While the scale of Kitchenware and Amul are obviously different, the fundamental need for digital solutions was the same. Yet, it was Amul’s access to and analysis of real-time data that helped it steer through the lockdown challenge.

Over the past decade, leading enterprises and organisations have increasingly adopted digital technologies. From deploying enterprise resource planning (ERP) to customer relationship management (CRM) solutions to creating mobile apps to digitally enabling the enterprise, organisations have adopted digital transformation frameworks as a way to reimagine themselves, staying competitive in their respective businesses and industries. Yet, most have only understood it to be about automating operations, and investments in the most critical area—data analytics—remain low. Niranjan Ramsunder, CTO of US-headquartered digital technology and transformation firm UST, says, “If we were to limit data-driven to simply mean advanced analytics, machine learning and other similar areas, then we could say that the data, analytics and ML-led projects would be around 40 per cent of the total spend [on digital transformation].”

But why is data analytics critical? “Digital transformation starts with data, but the increasing volume, velocity and variety of data makes it more and more complex to draw valuable insights and make informed decisions,” says Irina Ghose, COO of Microsoft India, adding that with data analytics, organisations can break down data silos and generate insights for better decision-making and, sometimes, even automate the decision-making process itself.

Industries are opening up to the concept of predictive analysis for future decision-making, but this is yet to accelerate. Accenture’s Business Futures 2021 report says 78 per cent of organisations in India have increased their use of both internal and external sources of real-time data over the past 12 months, yet only 43 per cent reported that people across their organisation consistently use real-time data in their day-to-day work.

Piyush N. Singh, Senior MD and Lead of India Market Unit at Accenture, says there are no specific industries that are racing ahead or lagging behind in digital transformation. “The reality is, in every industry, companies can be bucketed under three categories—leaders that are taking transformation seriously and are therefore investing holistically in the entire value chain; laggards that are only investing in parts of the value chain; and companies that are barely investing in digital transformation.” The leaders are still a minority—not more than 20 per cent in any industry—and they will surge ahead, he says.

By 2025, 180 zettabytes of data are expected to be created. Just how much is that? You are aware of a TB or terabyte—most PC hard drives have a capacity of 1TB or 2TB. Now, one zettabyte is one billion TB. Try and wrap your head around what 180ZB of data means.

This data explosion, albeit a bit scary, also presents enormous opportunities for businesses. Fuelled by this data, smarter organisations are infusing AI and the agility of the hybrid cloud to better predict and shape future outcomes and automate decisions. “By leveraging data as a strategic enterprise asset, companies can accelerate or scale digital transformation, and also contribute to high revenues and business growth,” says Kamal Singhani, Country Managing Partner for India/South Asia at IBM Consulting.

With digital transformation riding on data analysis, an enterprise can re-engineer, automate and infuse intelligence across key business functions. According to Harvard Business Review, such data-driven transformation can yield 54 per cent increase in revenue performance, 44 per cent faster time-to-market, and 62 per cent improvement in customer satisfaction.

Tight integration of data also highlights the organisation’s competencies and presents unlimited business opportunities. Satyakam Mohanty, Chief Product Officer of Fosfor by LTI (L&T Infotech), explains: “Insights derived from real-world data will allow you an (enterprise) to look farther into the future than you (normally) could. Instead of relying on day-by-day snapshots of your business, you’ll be able to set solid, measurable goals several years into the future.”

For example, Parle, India’s largest biscuit company, leveraged IBM’s hybrid cloud and AI capabilities, to get its products to market at the right time and in the right place. Sanjay Joshi, Head of Information Technology of Parle Products, says that the recent market dynamics “has necessitated the need to accelerate the innovation with digital platforms, drive resiliency in our supply chain, and augment decision support systems with AI”.

Apart from legacy enterprises, start-ups are also building their business models around data. B2B e-commerce platform Udaan is emerging as a preferred trade partner of established brands such as Apple and Samsung not just because of its reach in Tier II, III and IV towns, but also from the data insights it brings to the table—what options your customers considered, why were they considered, and which choices were made. How does this help? “The industry is able to identify and plan for SKU and brand preferences by region over lean and peak periods. Digitisation has also helped create predictive analysis on promotion planning,” says Hirendrakumar Rathod, Head of the Electronics Category at Udaan.

A common misconception among many organisations is that the cost involved for data-driven transformation is on the higher side, which Som Satsangi, Senior Vice President and MD of Hewlett-Packard Enterprise, India, clarifies: “Data-driven transformations drive digital transformations and, hence, the overall cost is typically part of the transformation itself. The difference, however, is in the way you prioritise and move ahead with your digital journey. We have seen that data-driven digital transformation is more successful.”

While data-driven transformation can be pivotal in enterprise growth, there are chances of failure, too. Enterprises need to strategically design a plan and invest in relevant tools and services. Enterprises often opt for a piecemeal approach and copy what worked for some other company or industry, but the technology solutions that worked for one company may not work for another. “Lack of visibility into current operations and traditional gut-based decision-making on transformation opportunities often leads to missing out the big rocks and instead focussing on pebbles,” says Sankara Subramanian, Partner for Lighthouse (Analytics, AI & Big Data) at KPMG in India. He adds that siloed initiatives and point solutions often miss the end-to-end view. Not aligning transformation with enterprise business strategy is one of the key reasons for the lack of impact. Another thumb rule is to invest in scaleable infrastructure, good quality data, and data-driven understanding of processes.

But to bring this transition into effect, not everything can be outsourced. Organisations need to strategically invest in the right training/skilling modules to empower their employees to work with these next-gen tools and meet their business goals. “Upskilling should be a priority from both an employer and employee perspective. Gartner estimates that by 2023, more than 33 per cent of large organisations will have analysts practising decision intelligence, including decision modelling. As business models and technology evolve, employees equipped with emerging technology skillsets will become vital for organisational success,” says Trideeb Roy, Director of Sales for Cloud Infrastructure & Software Group at Cisco India & SAARC.

It’s safe to say today that the future will hold data-oriented approaches to business strategy. The next decade of economic growth will be determined by today’s investments and the speed of digital transformation utilising data and analytics.