Understand the "WHY?"​ behind your numbers

Existing analytics solutions are failing to support business leaders of the 2020s in providing executives with the real-time insights they need to take the right actions at the right time. Although companies of any size start to realize that they need to make data the core behind every decision, nearly 70% of projects fail to deliver the desired business outcomes. The reason for that is that business analysts lack the tools to uncover uncertainty and the “why?” behind a company's KPIs. But the answers are there — hidden in (un-) structured data and organizational knowledge.

Working with over 100 executives, we realized one thing: companies need to reconsider how they think about data. While most firms start to collect store and aggregate data within their internal data lakes, what is considered as data is nearly just one kind of data: so-called hard data (Petersen 2004).

Hard data is what most people immediately identify as data: all the numbers companies can collect from sensors, financials such as last month's revenue, stock prices, or all of those numbers your controlling team is crunching in their day-to-day business.

But there is another kind of data. One that is many times not even considered as such: soft data. This type of data is unstructured, often subjective, and mainly stored in the heads of people. Their emotions, experience, need, and opinions. Soft data is much harder to put in numbers and therefore most of the time not used in any kind of data-driven decision-making in a company. However, this data is the most valuable and important one to empower managers to make better decisions faster. It is the data that explains the causality, why behind your firm's performance outcomes (Dellermann 2020).

For example, in times of COVID-19, your EBIT is not declining because your revenue went down, or your costs are too high (well, actually it is, but that's just the tip of the iceberg). There is some causal mechanic behind this phenomenon that is measurable just with soft data. For example, your revenue is declining because the needs and attitudes of your customers are shifting, they experience fear of losing their job and therefore spend less money on your products. Or your company is losing market share due to emerging technologies and trends that customers consider more innovative. On the other hand, your costs are not too high because you spend too much money on salaries and therefore can resolve this by cutting jobs. Most of the time it's something deeper. Your employee's productivity suffers from a lack of digital tools to collaborate remotely, from emotional with how executives deal with the crisis.

And nearly every time companies are failing to innovate their business model, it is not a lack of skills of capabilities. It's a matter of not sensing what customers want, which market to address, or inappropriate firm culture.

Especially when it comes to strategic decisions, executives need to realize that it is no longer enough to use static quarterly reports, manual data analysis of financial number or isolated consulting projects to steer their company towards success.

Winners will reinvent themselves with putting AI at the core of their business, continuously sensing weak signals from the market, their customers, and their employees and understand that soft data is giving them the answers. To take the right actions at the right time. Winners will transform their organization to the Intelligent Enterprise - powered by human intuition, augmented by AI.

References

Accenture (2019): The power of the data-driven enterprise.

Dellermann, Dominik (2020): Accelerating Entrepreneurial Decision- Making with Hybrid Intelligence: Design Paradigms and Principles for Decision Augmentation. Kindle Direct Publishing.

Petersen, M. (2004): Hard and Soft Information: Implications for Finance and Financial Research. Working Paper, Northwestern University.

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