Advanced analytics: A model answer

By James Walker 

More than half of companies that invested over £10m in analytics outperformed their peers – double the proportion of those who invested £4-£10m.

Big data analytics has unleashed a wave of change throughout the business world and is now on the tip of every CEO’s tongue. We often hear about how analytics has transformed outcomes for businesses across sectors; whether it’s delivering ultra-personalised customer services, predicting consumer behaviour, or boosting productivity through automation.

Everyone wants a piece of the action, and companies are investing heavily in the rush not to be left behind. British businesses plan to double their current spending on analytics from £12bn to £24bn by 2020, while in the US it’s a similar story, with investment expected to increase from £58bn to £112bn.

And there is good reason to spend big. Our research, laid out in ‘Putting Analytics to Work’, shows that 52 per cent of companies that invested over £10m in analytics outperformed their peers – double the proportion of those who invested £4-£10m.

But while there is a clear link between the value invested in analytics and overall performance, this doesn’t tell the full story. The reality is that many attempts to build analytics into a business fall flat, with only 20 per cent of companies reporting a significantly positive commercial impact from their efforts. This was the catalyst for our report – what actually are the conditions for a successful analytics capability to flourish?

It may be common knowledge that capitalising on big data has the potential to impart a competitive advantage, but what is less well known is how to actually make analytics successful in the long term. This not only requires significant investment, but also ensuring the right conditions are in place.

Building the foundations

At a foundational level, obtaining support from the top of the organisation is critical. The CEO must champion analytics and drive the various changes needed across the business to make it work. This is reflected in the research, which finds that over half of top performing companies believe their senior leaders support progress in analytics. The patience to remain committed to the transformation over the long term is also essential to prevent fledgling efforts from fizzling out.

And crucially, the development of the analytics capability must be aligned with the overall business goals from day one to ensure analytics is being deployed in the right place to make a commercial impact. One thing analytics should not be is a hammer looking for a nail.

Pillars of success

On top of this foundation sit five imperatives that all contribute to enabling successful analytics. The most critical of these is ensuring the analytics capability is substantial enough to make a tangible impact that can be sustained. Small-scale pilot projects and ‘proof of concepts’ will quickly wither and die without the oxygen of broad support and adoption. Almost 70 per cent of the best performing companies have a centralised analytics capability, which is better placed to address problems from across the business and inform more pivotal strategic decisions.

In addition to having a central hub, analytics is most successful when it’s embedded into the organisation’s entire eco-system. That means all departments must be willing to change their processes to maximise analytics input, which in turn helps to identify the key pivot points where analytics can make the biggest difference.

For many people, the most obvious enabler of analytics is perhaps technology, which is often also the main trigger for investment; for example, when a company digitalises customer services. Technological applications – such as automating manual processes - also help embed analytics into an organisation. But technology isn’t much use if you’re not using the right data, which is why data quality is another key pillar of analytics success.

Ultimately, the analytics capability must continuously evolve over time to reflect wider changes taking place across the business and operating environment. A regular feedback and review process therefore has a key role to play in making sure analytics continues to boost the bottom line.  

Empowering people in a data-friendly culture

All of these elements must be woven into a culture that is informed about the potential of data, that encourages discovery and trust, and that ultimately embraces analytics as an integral part of everyday work. Our research confirms this, with about 80 per cent of meetings in the best performing companies including analytics or data elements.

Furthermore, both the providers and consumers of analytics must be informed about the value of analytics and how to take advantage of it. This means training the analysts about what the business needs, and training the business about how to benefit from the analysis.

From a talent standpoint, the analysts themselves must have a deep understanding of the commercial challenges facing the business and the ability to structure a technical solution accordingly. Our research suggests this is the real talent-related challenge for businesses trying to leverage big data analytics, as opposed to a global ‘drought’ of data scientists, which is often thought to be the problem. 

These imperatives also align with a general preference among companies to employ a pool of specialised people who are focused on tackling key questions, rather than equipping everyone with self-service analytics tools.

Considerations for business leaders

Advanced analytics is clearly here to stay. It sharpens the competitive edge for the best performers across the value chain and boosts sales and profits for those who adopt it. And as investment in analytics grows across sectors, the gap between the top and poor performers will only widen.

But investing money in analytics without adhering to at least some of the key conditions for success, such as having senior backing and changing culture, is likely to yield poor results.

CEOs embarking on a mission to build or expand their organisation’s analytics capabilities should start by asking their teams some important questions, including:

·         How can we improve the analytics capability given what we have available?
·         Which of the 10 imperatives should we focus on and in what order?
·         Which aspects can we accelerate with external support?

Finding the answers to those questions and allocating the right level of investment will help pave the way for success with analytics and for the organisation as a whole.