Most businesses in the digital age are exploring the benefits of data-driven initiatives. However, securing payoff can be more complicated than most businesses believe.
It’s one thing to collect enormous volumes of data and apply analytics to it; many businesses do so. It’s another thing entirely to get the most out of that data and analysis in terms of business value.
Enterprises that have made significant investments in analytics technologies may be doing so without determining how to ensure that their efforts yield commercial value. This could be the result of a variety of factors.
Here are some pointers on how to make sure that analytics efforts pay off by giving actionable insights rather than merely producing attractive reports that don’t say much.
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A key IT leader mandate in generating more value from data is to better align IT initiatives with the organization’s business goals. Real-world business difficulties necessitate the use of data analytics. Starting with business-specific use cases can be a good way to get buy-in from more stakeholders who aren’t necessarily in IT.
Because the data is delivering unambiguous results that are understandable in business terms, this method lets the rest of the company see the value across various functional areas and business units.
To uncover real-world victories and internal use cases, IT and data analysts must collaborate with business units. This helps everyone comprehend the true worth of getting there and the benefits of working together to get there.
Having executive sponsors or stakeholders who can advocate for data analytics outputs and insights might help to generate more value. This executive champion helps to drive adoption throughout the enterprise and can help to shape the operating model so that people can act on the insights gleaned from the analytics.
The company can begin to activate the findings and gain value from them if there is a high level of buy-in and support. The company will not realise any value if all that is done is to create a report based on the findings and no action is taken. The data will yield insights, which will be used to make business decisions at all levels of a company, from tactical to strategic.
Despite the fact that the desire to be data-centric is widespread among businesses in the digital age, many still fail to see the full worth of data. Companies must transition away from acting on gut instinct and toward being insights- and data-driven enterprises.
With a clearer route and vision of how to reach their goals, a data-driven operational model increases the likelihood of success and enables enterprises to get value from their data analytics faster.
Companies, however, require a framework to measure success in order to recognize the value derived from a specific insight or piece of data. This enables them to review their current progress, make necessary improvements, and optimize their progress toward their data analytics objectives. It will assist data executives to illustrate the return on any analytics investment by showcasing the amount of value and results created by data analytics through a clear measurement capability.
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To assure value through higher-quality data, the analytics team should collaborate with business users on a regular basis – or incorporate business users as members of their cross-functional teams.
Close collaboration also ensures that the data team develops business intuition in order to better understand how the data they manage is used in practise. As a result, the team can be more self-sufficient and make better judgments on accuracy, accessibility, and scalability depending on business requirements.
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Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.
