The Strain on Data Supply Chains: Why Data Democratization is a Priority

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Building stronger data supply chains will ultimately create a positive impact for the business and its key stakeholders.

While the coronavirus pandemic has introduced uncertainties and fluidity across industry and economic landscapes, there is one thing we know without a doubt: many businesses will be permanently transformed by changes to their data supply chains. As the extreme toll of the coronavirus spread across the world, the ensuing shutdowns and stay-at-home orders in country after country roiled businesses, shifting the focus to business resilience and adaptability, while staying true to enterprise purpose. Many adjusted to the new realities by putting tremendous pressure on IT departments and chief data officers (CDOs) to provide employees and business partners access to information as soon as possible, essentially trying to democratize data in the blink of an eye.

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Data democratization – giving an entire organization and its ecosystem of partners and suppliers access to easy-to-understand information – has long been cited as the way to unlock value from the vast data-sets organizations maintain. Effective access to information is essential to entering new markets, unleashing new opportunities, and strengthening the data supply chain. And in the face of the pandemic, data supply chains have become absolutely essential to drive accelerated business outcomes for every stakeholder in the value chain.

What Got Us Here  

As businesses were forced to close premises and employees moved to remote working, business leaders across the value chain also found their access to data – from within the enterprise and even across the entire ecosystem – rapidly restricted. Information on market demand, operations, production, supply chain, and logistics, people, finance – all critical to making business decisions and all often residing in siloed functional or organizational applications – suddenly became inaccessible. Disruptions in the data supply chain created inventory imbalances, overwhelmed online services, stressed information infrastructures, and disrupted physical supply chains.

Building More Links

It quickly became clear that data supply chains not only needed shoring up but also needed additional intelligence to navigate the new business realities brought on by the pandemic. Reliable, immediately accessible data is built on sophisticated algorithms to predict changes in product demand. It is also what allows companies to predict demand with greater confidence from across the business’ ecosystem. And, it’s what enables enterprises to be more responsive to changing market conditions, managing efficiency, and cost more effectively in the process.

Fortunately, many technology and data management leaders had already invested in digital transformation programs, with a core component of that effort being digitizing the data supply chain and democratizing data. Now that investment is proving to be vital.

As major food and big-box retailers experienced panic buying, it became necessary to identify and track consumer packaged goods more narrowly than in pre-pandemic conditions. Major retailers needed to forecast what inventories would look like, not just three days into the future but a full week ahead. Without access to the relevant data supply chain, businesses experienced sudden shortages and a general unpreparedness to meet demand. To prepare for and prevent such eventualities, business intelligence needs to be integrated into supply chain dashboards to trigger alerts about inventory and supply disruptions.

Such business intelligence also is needed to help companies become more responsive and adaptable to market dynamics. Grocery store chains, for example, can share information across different ecosystem partners, enabling them to make smarter forecasting and buying decisions. By correlating changes in consumer locations and behaviors – from shifting commuting patterns to eating more protein – retailers can forecast demand much farther into the future.

Even systems that seemed built to handle large volumes of digital transactions, such as in the financial services sector, were pushed beyond capacity in the wake of the COVID-19 crisis. The surge in loan applications overwhelmed lenders handling the Small Business Administration’s Paycheck Protection Program in the U.S. But by building and strengthening the robustness of their data supply chains, integrating data from across applications and enterprises, institutions can use new analytics capabilities to automatically monitor credit criteria and identify at-risk customers, easing the burden of managing transactions and increasing the speed and resilience of their systems in the process.

Further, business intelligence can also be used to assess system performance. For example, businesses can use this intelligence to develop new scenarios to meet – and improve – service level agreements in critical areas such as healthcare.

Moving Ahead, Using Lessons of the Recent Past

With many CDOs and their teams now on the other side of the acute phase of the pandemic, it is time to take more measured steps to refine their data democratization processes so they can fortify their data supply chains.

To improve data-sharing across departments and between approved ecosystem partners and suppliers, IT departments need to fortify the reliability of these data supply systems by focusing on security, ethics, and proper governance. In particular, there are six factors IT must consider:  

  • Ethics: IT needs to help teams be transparent about the intent of collecting and sharing data to ensure the success of any project. These goals should be frequently monitored and reiterated.
  • Privacy: Teams need to adhere to the privacy norms IT sets to protect personally identifiable information and to maintain stakeholder confidence.
  • Trust: To avoid “trust deficits,” enterprises need to reassure all parties – especially regulators – about how information will be used in the data supply chain and how the company will manage best practices.
  • Legal: A dedicated legal team needs to be established to support IT and oversee regulations and data-related legal risks.
  • Risk: IT needs to acknowledge that data sharing involves an element of risk while taking steps to minimize the possible negative impact for the company, its suppliers, and their joint customers.
  • Value: Data is expensive to obtain, so democratization should only be undertaken when it will add brand value, as well as honor security and support the moral values and purpose a company has established. It should not be taken on at any cost.

Another critical dimension is the need for more comprehensive and responsible reporting backed by confidence in the data supply chain across the value ecosystem. As companies shift to purpose-centricity and the need to demonstrate a commitment to stakeholder value, the role of data will become increasingly critical.  From ethical supply chains to carbon footprint and sustainable operations to lower emissions, enterprises are leveraging robust data maturity models to identify opportunities to drive positive change.

Forging Future Success

Building stronger data supply chains will ultimately create a positive impact for the business and its key stakeholders. Indeed, there are countless positive pre-pandemic examples ranging from drug companies that have used data democratization to achieve better, faster data flow in clinical trials to bring life-saving drugs to market to energy firms that have reinforced their data supply chains to improve the efficient production and transportation of natural resources.

Data democratization needs to continue to strengthen the data supply chain as we get through the next phases of the COVID-19 pandemic. And, with companies from Twitter to Nationwide, the giant U.S. insurance firm already extending work from home practices, we are looking at a new beginning in terms of collaborative working and data sharing. For CDOs and IT leaders, this new beginning offers a great opportunity – to drive data democratization across the business ecosystem to empower and enable stakeholders to make smarter, more informed decisions as they build more resilient and adaptable enterprises.

Dina Kholkar

About Dina Kholkar

Dina Kholkar is Vice President & Global Head, Analytics & Insights at Tata Consultancy Services (TCS). In this role, Dina guides some of the world’s best companies in their journeys to unlock the potential of their data through the power of analytics and artificial intelligence (AI) to uncover new business opportunities, drive business growth and increase revenue streams. Dina advocates ‘data centricity’ as a strategic lever for business growth and transformation and believes that the need of the hour is ‘evangelization’ of data & analytics. His thought leadership in addition to his team’s expertise and collaborative working with customer organizations is empowering them to realize the power of their data in real-time decision making and ensuring success in their Business 4.0 transformation journeys.

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