What data analytics should you use to inform your corporate strategy?

?? In my experience, the scope of descriptive analytics extends beyond mere data summarization. ?? Data Aggregation Descriptive analytics aggregates data, offering a comprehensive view of performance, aiding trend identification. ?? Visualization Techniques Advanced visuals simplify complex data, aiding effective insights communication. ?? Feedback Loop Descriptive analytics offers continual insights for tracking change effectiveness over time. ?? While descriptive analytics is often seen as a basic form, its depth in aggregating diverse data, advanced visualization, and providing continuous feedback makes it indispensable in informing corporate strategies.

Descriptive analytics are great to see where you were and your progressed through that journey. They identify what worked and what didn’t work. I believe to mold corporate strategy you must look at forward indicators and the data sets which comprise them. Customer sentiment, technology roadmaps, market trajectory, etc. As an example, can you imagine what happened to people servicing the DVD market if they weren’t paying attention to the online services which were creating video on demand products for the consumer? I can tell you what happened to some of them - they got caught with their pants down and it tanked their business because they didn’t look ahead.

To shape my corporate strategy, I employ a comprehensive data analytics approach. Descriptive analytics reveals past performance, diagnostic analytics uncovers reasons behind results, and predictive analytics anticipates future trends. Customer data, market research, and competitive intelligence offer insights into behavior, trends, and positioning. Sentiment analysis gauges public opinion. In essence, integrating analytics, customer data, research, competitive analysis, and sentiment analysis creates a robust framework for informed strategy decisions.

What data analytics to inform your corporate strategy revolves around a basic understanding of the business environment. The analytics must take into consideration the corporate objectives and key performance indicators (KPIs) which should be in line with stakeholder expectations. Data collection, analysis and reporting should form a basis for developing standard operating procedures (SOP) for the organisation. The metrics should serve as benchmarks for measuring progress in line with the strategic objectives.

In my opinion, utilising AI in predictive analytics informs corporate strategy by leveraging data-driven insights to make informed decisions. By analyzing patterns, trends, and potential outcomes, AI helps organizations anticipate market shifts, customer behavior, and competitive landscapes. This foresight enables proactive decision-making, allowing companies to identify growth opportunities, mitigate risks, and optimize resource allocation. Ultimately, incorporating AI in predictive analytics empowers corporate leaders to develop agile and adaptive strategies that align with the dynamic business environment, fostering a competitive edge and sustainable success.

This is an interesting question but is it the tail wagging the dog? The corporate strategy should deliver the vision therefore the analytics should support the delivery of the strategy - so consequently in determining what the organisation is looking to achieve the analytics should monitor the activities that are needed to deliver on the strategy.

To (loosely) quote Cassy Kozyrkov, the key is to understand what data is going to change your decision. Historic data doesn’t always predict the future, and predictive analysis depends on the data you have available now, not later. So to drive your strategy, focus on what information will convince you to change that strategy.

Maintaining a flexible corporate strategy in response to industry trends and market realities is crucial. The strategic use of data becomes pivotal in defining the most effective approach to optimize market adoption. The choice of data analytics should be aligned with the current engagement stage of the business model and the market landscape. ????