Prof. Yudhvir Seetharam,
In a world flooded with data, the ability to effectively apply this vast resource is a defining factor for business success. However, merely possessing reams of data is insufficient; businesses must strategically apply it towards sustainable growth and achieving their core purpose.
The effective use of data starts with analysis, which fundamentally depends on asking the right questions. This is no straightforward task, given that few businesses can today afford the luxury of extensive exploratory data analysis. The frenetic pace, intense competitive pressures, and soaring costs associated with data analysis render such an approach untenable. Instead, businesses need to have a laser-sharp focus when it comes to interrogating their data, knowing precisely what they’re looking for and having a plan to extract it. While success in this regard will look different for every business, several core principles need to be considered to maximise the potential for data analysis effectiveness:
1. Navigate the paradox of choice – One of the biggest hurdles businesses face when analysing data is simply having too many options, which then leads to what has become known as “analysis paralysis.” To avoid this pitfall, organisations must narrow down their objectives and frame well-defined questions. For example, when leveraging data to avoid customer attrition, open-ended queries like “Who is most likely to leave?” are less actionable than specific ones like “Which customers considering leaving would respond to a promotion?” Having too many choices, whether in terms of objectives, visions, or poorly defined goals, can hinder analysis and prevent effective decision-making. The only way to navigate this paradox is by precisely defining your analytical aims.
2. Define a clear vision – Following on from principle 1, achieving specificity and relevance in data analysis demands that businesses start with the end in mind. Before embarking on any project, it’s crucial to have a clear vision of the desired outcome. Are you looking to boost sales, understand client motivations, deepen customer relationships, or address a specific internal requirement? Each objective necessitates a distinct approach to data and analytics.
3. Align with your core purpose – A common pitfall businesses encounter is a lack of clarity about what they truly need from their data. Overcoming this challenge often requires stepping back and revisiting the bigger picture – the vision and purpose of the business. This re-orientation isn’t just about gaining perspective; it’s about grounding the project in the organisation’s core mission, which should guide all interactions with data. For example, the core purpose of FNB is to deliver meaningful help to customers. This mission informs the kinds of questions the bank asks of its data, focusing on enhancing the ability to serve customers and communities rather than solely pursuing business metrics like sales or efficiency. While purpose-driven data analysis inevitably improves these metrics, they should be viewed as by-products rather than the key focus. If business metrics are the sole desired outcome, the chances are high of missing the mark altogether. True value comes from extracting meaningful, relevant insights that go beyond surface-level metrics to fulfil the deeper purpose of the business and better serve stakeholders. This is what will distinguish leading businesses and afford them a competitive edge.
4. Tailor approaches and outcomes to your unique context – Data analysis outcomes must be tailored to the specific needs and context of the business. Every organisation is unique, with its own culture, customer base, and market challenges. As such, the data strategy and analytical approach must be equally unique, guided by these individual factors rather than blindly following trends that may not apply. Success lies not in keeping up with other businesses, but in finding your own path, using data to better serve your customers and improve operations in a way that resonates with your distinct identity.
5. Overcome the fear of choice by embracing first principles – Given the speed at which the business landscape is evolving, there are bound to be scenarios where historical data is unavailable to guide decision-making, such as when introducing an entirely new product or service. In these cases, businesses need to approach data analysis from a foundation of “first principles” – logic and intuition – rather than relying solely on data. This doesn’t negate the importance of data; it merely acknowledges that there are certain challenges where data-driven insights are insufficient. First principles can provide a foundational direction that data can later support or contradict. This helps to overcome the fear of being wrong, which typically drives the formulation of “straw man” arguments just to validate assumptions – an approach that runs a very high risk of actually hindering progress.
As the stellar rise of AI continues to level the business playing field, winning organisations will be those with a genuine commitment to using data strategically – not just as a business asset, but as a tool to enhance the delivery of its core purpose and brand promises. Those who recognise this fundamental shift will be well-positioned to lead in this digital age, unlocking maximum value from their data to deliver on the all-important success requirements of better customer service and experiences.
Prof. Yudhvir Seetharam, Head of Analytics, Insights and Research for FNB Business. He writes in his personal capacity.
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