About 94% of business leaders around the world say that the management of their company is prepared to make significant decisions about the strategic direction of their business, but barely one-third relied primarily on data and analytics when they made their last big decision.
According to Gut & Gigabytes: Capitalising on the Art & Science in Decision Making, a new Economist Intelligence Unit Survey sponsored by PricewaterhouseCoopers, highly data-driven companies are three times more likely to report significant improvement in making big decisions, but only one in three executives say their organisation is highly data-driven.
Executives’ intuition or experience and the advice and experience of others in their organisation were the decision making modes of choice for 58% of executives.
However, 43% of executives that say their companies are highly data-driven report the biggest improvements in decision making over the last two years.
All executives said top priority over the next two years is to make investments in the quality of data analysis to make better decisions.
More big decisions are made opportunistically than deliberately, and big decisions have big impact on future profitability; nearly 1 in 3 executives value those decisions at $1 billion plus.
Crucial Issues
Executives make big decisions frequently and review them often, over three quarters of executives make a big decision each quarter and 43% review them every month. Many executives are sceptical or frustrated by the practical application of data and analytics for big decisions.
The Survey found that the five most important decisions facing executives in the next 12 months are, in order: growing the existing business, collaborating with competitors, shrinking the existing business, entering a new industry or starting a new business, and corporate financing.
How good a company is at making big decisions will determine their success and while we see executives continuing to rely on experience, advice, or their gut instinct, they can also see that investment in data and analytics is crucial for the success of a business.
Their experience and intuition and using data and analytics should not be mutually exclusive.
Executives must respond to the challenge as to how best to marry the two.
They know the right questions; they now need to get the right answers using data from the last two years to inform their decisions.
Motivating factors
Executives said the appearance of a business opportunity they could not ignore was the most common motivation for considering a big decision (30%). Other reasons: making decisions that were previously delayed (25%), strategic fit (18%), testing ideas (15%), reacting to external factors (9%), and regulation (4%).
Despite the comfort of executives in relying on gut instinct, nearly two-thirds (63%) said that the use of data has changed how their company makes decisions and they expect it to have more impact in the future.
The top three changes executives plan in decision making include the number of people involved in making a decision, greater use of specialised and enhanced analytics and data analysis, and the use of dedicated data teams to inform strategic decisions.
With the impact of big decisions on profitability, often valued in the billions of dollars, and the lack of predictability of when decisions need to be made and when, companies are trying to increase the speed and sophistication of their decision making. This requires using newly accessible data and analytic techniques, and clarifying accountability in the decision making process.
Balanced Approach
The Survey findings affirm a balanced approach to using data and analytics to make speedy and sophisticated big decisions for competitive advantage.
These include (a) Mapping decisions to shareholder value by pinpointing decisions that have the biggest impact on the company’s future (b) Linking the strategic alternatives to business impacts by simulating how mega trends, industry trends and the strategic alternatives affect the business and operating model (c) Applying a value and results lens by quantifying the expected improvement in metrics associated with improving decision making (d) Adopting a structured test and learn approach by specifying changes to the organisation, process, technology and culture that are needed to improve decision making
Colum Rice is Partner and Head of Business Intelligence and Analytics at PricewaterhouseCoopers based in Auckland
