With a tagline of the “power to know”, SAS is determined to help its customers use data and analytics to make better decisions. I caught up with Philip Reschke, Head of Analytics Strategy and Innovation for the Nordics, to learn more about his views on what it means to “run an insight-driven business”.

You work with business executives who want to deploy analytics to enhance or maintain their competitive edge. What are the most common barriers?

As the global economy becomes increasingly digital, business success requires companies to be able to enhance customer experience, differentiate products and services, and optimise operations using data and analytics. There is a tremendous amount of hype around artificial intelligence and machine learning, and organisations are rushing to invest in technology and data scientists. Despite these investments, many organisations are still struggling to generate actionable insights and scale their decision-making capabilities. Today’s hugely successful businesses (e.g. Amazon or Google) can bring actionable insight into almost every decision they make to create competitive advantages across the customer lifecycle and business value chain. In other words, they can contextualise every decision, and optimise their business model and the design of their products, services and operations as a result.

So this is mostly about decision-making?

Yes, mostly. Making fast decisions is not difficult, but making fast and informed decisions when the opportunity presents itself, in real-time, is. E.g., each typical customer interaction involves a cascade of choices, and to be relevant, companies need to take a relevant ‘next best action’ on every customer interaction – irrespective of the channel the customer prefers to interact through. There is also the challenge of accessibility—customer self-service has driven a change in responsiveness that means that companies are ‘always open’, and need to be able to respond immediately, whatever the time.

Surely this means employees at the “coal face” need to be more empowered?

Yes, absolutely! This is a massive cultural change. Successful companies embed data and data-driven decisions in their DNA — it is simply how they do business. They are customer-focused and make sure that this focus extends to people, processes and technology to create a culture of insight-driven decision-making from top to bottom. CEOs must shape an operating model that relies on decision-making logic embedded into the operational software to ensure that insight is always actionable. Members of the C-suite must foster a culture of experimentation and continued learning, and strategically invest in decision-making capabilities that enhance the value of data and analytics.

Successful companies embed data and data-driven decisions in their DNA — it is simply how they do business. #analytics Click To Tweet

How do you help organisations get to this level of maturity?

My team and I use a series of approaches to help organisations align people, processes and technology. We start with a series of maturity assessments, to see how ready the organisation is to make use of data. Then we make recommendations and finally, we help them, often together with partners, to implement supporting technologies, suggest organisational changes to, e.g. how the business organise its analytical talent, how business and IT collaborate, and so on. It is a matter of education and re-mapping how decisions are made. Our goal is to help our customers develop capabilities that will enable them to derive insights that shape business decisions, improve customer experiences and create innovation at the required scale to gain a lead over their competitors.

Is data relevant for all types of decisions?

Well, analytics are ultimately most useful for the tactical or operational decisions because that is where most of the data is available. The big strategic decisions — business units or regions on which to concentrate, for example — are fairly few and far between from a volume perspective, not that analytics does not add value to support strategic decisions. The vast majority of data is useful for day-to-day, if not minute-to-minute, operational work, where you need to make decisions at scale. There are plenty of good examples of this in practice, including in the public sector and commercial organisations.

How do you describe the value of good decisions?

Placing a value on analytics can sometimes, depending on the decision, be hard. Ultimately, a business has certain KPIs they track to measure the performance of their operations. Any decision that can be improved, whether more accurate or made faster with analytics, is potentially worth exploring. We operate in an increasingly dynamic world where almost every company faces global competition, so the need to make agile decisions is no longer “nice to have”, it is a “must have”. The ultimate consequence of making too many wrong decisions or not being able to respond in time is extinction. It is not a coincidence that the average lifespan of an S&P 500 company has dropped from 55 to about 20 years since 1960.

Philip, thank you very much!