How To Build A Data &#038; Analytics Strategy For Your Business
As lockdown measures are eased and professionals prepare to go back to work, businesses are looking to adapt to an increasingly uncertain and complex environment. With the pressure to stabilise their finances and operations peaking, data-driven analytics have been offering much-needed succour to organisations. However, approaching analytics can be daunting – not only is collecting and curating data tough, but it can also be just as challenging to glean useful insights from it. This demands that organisations build a robust AI-powered analytics strategy that would inform and drive all their decision making. What is the right approach that companies need to take to make prudent decisions using smart analytics? As elucidated by IT giant Wipro, there can be a four-pronged approach to this – one that ties together business, analytics, technology, and capabilities. Let us dive in. Business: Outline Clear Goals Every business process produces actionable data that may (or may not) provide insights to align with your organisation’s goals, and the vision the business has created for itself. To optimise this data effectively, companies need to revisit their strategies and ensure that it is in congruence with the new normal brought in by the Covid-19 pandemic. Go back to the drawing board and chalk out what the new opportunities could be in this reality. A good place to start will be to first acknowledge your current capabilities and identify areas where real business value can be created. While some companies may need to entirely pivot to survive, others may be successful in keeping afloat with some minor restructuring within the organisation. Both would demand new goals, and different metrics and benchmarks to measure success. This would be the first step in the journey to building and implementing a robust data and analytics strategy. This would not only enable you to get the most out of the current situation, but also provide a clear framework to anchor all decisions around, as well as help measure progress along the way. ALSO READ: Are Analytics Jobs Recession-Proof? Here’s What Data Scientists Think Analytics: Assess Your Data Needs Once your company has outlined clear goals for itself, ensuring high-quality data and choosing the ones you want to use is the next step. Understand how you can maximise the value of available data and use it to support your new business objectives. Since all your business processes have generated a lot of data, sieving out the ones that you can use to bolster your new business model is critical. While it may be true that all kinds of data can lend some degree of value to a business, identifying your priorities and anchoring your analytics implementation plan around it is important, especially when dealing with limited resources. A good place to start would be to work backwards and assess your company’s data needs. Ask yourself what insights would help you boost certain critical functions in your current business model while keeping in mind key performance indicators. Technology: Choose Corresponding Tools After laying out your new business goals and assessing your data requirements to meet those objectives, the next step would be to identify the business analytics tools that would enable the latter. While you may already have a business analytics implementation plan in place, it may be prudent to retool and have a checklist ready based on your new goals and needs. Many big tech corporations have a strong suite of business analytics software to enhance your decision-making capabilities, including SAS, IBM and more. Based on your company’s unique requirements – borne from the first two steps – you need to choose one (or more) that will serve your business interests. For instance, IBM offers several tools based on where you choose to deploy your business analytics – be it for budgeting and financial planning, or for operationalisation, productivity and other processes. No two business analytics software vendors would be the same, and you should choose a competent set of tools – ones that can enable your analytical capabilities and support you well based on your specific use-cases. ALSO READ: How Small Businesses & Startups Can Utilise AI To Survive The Pandemic Capabilities: Foster Right Skills Through Reskilling With many companies laying off employees to withstand some of the shocks of the impact caused by the Covid-19 pandemic, skilled staff is short. Thus, it behoves that you ask yourself what is the breadth of expertise your organisation needs today to enable these new analytical-based processes. While technological advancements will enable companies to leverage their vast cache of data, their workforce will still remain a critical strategic asset in their overall business analytics plans. Your strategy needs to factor in the development of some key skills among existing employees that would enable them to assist in the overall analytics cycle. There are many courses – some of which are even available for free – that businesses can include as part of their internal training processes to grow their talent pool from within, rather than turn to expensive hires. Thus, while technology will spearhead an organisation’s entry into a more data-driven culture, it is critical to strike the right balance with the right talent to gain a competitive advantage in these uncertain times. Outlook With a proper goal (that factors in the new normal) in place and a clear understanding of the company’s data, tech and talent needs, a truly successful business analytics strategy can be deployed. Each piece of this four-pronged approach is as critical as the other and could mean the difference between your organisation’s ability to make data-driven decisions, or not.
As lockdown measures are eased and professionals prepare to go back to work, businesses are looking to adapt to an increasingly uncertain and complex environment. With the pressure to stabilise their finances and operations peaking, data-driven analytics have been offering much-needed succour to organisations. However, approaching analytics can be daunting – not only is collecting […]
What is the right approach that companies need to take to make prudent decisions using smart data and analytics?
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Anu is a writer who stews in existential angst and actively seeks what’s broken. Lover of avant-garde films and BoJack Horseman fan theories, she has previously worked for Economic Times. Contact: anu.thomas@analyticsindiamag.com