The evidence of the profitable impact of data on decision-making is undeniable — largely because it is based upon real data.

As early as 2013, research by Andrew McAfee and his team at Centre for Digital Business found that the organisations most strongly focused on data-driven decision making had four per cent higher productivity overall and six per cent higher profits. In other words, a quantifiable, significant edge over the competition.

By 2015 Gartner, in its Data-Driven Marketing Survey, was suggesting that marketers expected most of their decisions to be quantitatively driven by 2017 and that, as a result, most companies planned on growing their analytics teams.

The proof of Gartner’s assessment was clear in the rising demand for analytics talent. Take the IAPA Australia salary surveys over the last few years — these have shown an undeniable upward curve in the money companies are willing to pay the top data analytics professionals, which in some specialist categories has broken through the $200,000 mark.

The sums companies are investing are impressive. IDC, for instance, revealed its own analysis suggesting top Australian companies will likely spend as much as $2.7 billion this year building analytics capabilities within their organisations.

A recent study by Boston Consulting Group (BCG) found that “data-led” organisations can expect to see 20 to 30 per cent EBITDA gains over companies that have not embraced data-driven decision-making. The authors of that report found organisations that chose to leverage data also delivered improved staff and customer satisfaction, increased innovation and reduced operating risk.

However, even though there is a strong optimistic streak around the shift to data-driven decision-making, there are also voices of caution. Partly this is because the challenges of making a transition to a data-led way of working are significant.

Anna Russell, director of Polynomial, writing in Which-50 last year, noted “The cultural impediments to data-centricity are rarely a lack of will, or the presence of active ‘blockers’ within the organisation. Instead, they tend to revolve around an absence of proactive intent, and the failure to realise that shifting organisational mindset in a fundamental way is a large task that takes considerable sweat equity.”

In other words, the shift is not easy.

There is also a danger that, in their desire to prove their data credentials, companies lose sight of an important point: the data itself is less important than its purpose. And its purpose is making life easier for customers.

Gartner analyst Andrew White describes “data-driven” as a dangerous catch phrase. “Data, or even technology, for its own sake without a clear line of sight to an outcome — social or business — is a terrible waste.”

Rather, success looks like better-serviced customers.

It is a message that resonated with the Commonwealth Bank, for one. Last year the bank introduced a new service for its business clients called DailyIQ.

At the time, Adam Bennett, Group Executive, Business and Private Banking, Commonwealth Bank, said “By providing businesses with data-driven insights we’re helping them make better decisions on how to optimise their finances, where to expand, where to target marketing, when to optimise staffing, and where to increase customer loyalty.

“The reality for many businesses is that data can be hard to get and even harder to analyse. Daily IQ is putting actionable insights directly into the hands of businesses — helping them make informed decisions to enhance their performance and productivity.”

Better experiences

Business analysts and product owners need to tell the stories found in the data to other stakeholders in the business, who can then turn those insights into better experiences for customers.

Richard Ng, Marketing Director APAC at Tableau

By combining feedback from customers — both direct feedback and data generated by their interactions with the brand — organisations can build a more fully formed picture of how service delivery affects the customer experience, performance and future behaviour.

According to Richard Ng, Marketing Director, APAC, of Tableau, “Finding raw data to work with shouldn’t be a problem. These days there is a proliferation of customer experience channels generating vast amounts of data. Every call to the contact centre, every service request, every visitor to your web site and every time a product is shipped contributes to the store of available data.”

He said the difficult part is bringing all the data together in a way that facilitates analysis. However, marketers need real-time data to fully know customers’ context, and orchestrate the most meaningful experiences for them.

“An example of this is the annual Tableau Conference held in the US. Insights into the data gathered from participants in attendance each year have enabled us to optimise the overall conference experience by understanding that customers want to learn but also to network and have a fun and memorable experience.”

Success in all marketing programs, however, relies on an integrated customer analytics strategy that puts quality data and its resulting insights in the hands of decision makers, says Ng. “Under-utilising data may leave customer experience failing to achieve your desired outcomes.”

 

About the author

Andrew Birmingham is the director of the Which-50 Digital Intelligence Unit of which Tableau is a member. Members provide their insights and expertise for the benefits of our readers. Membership fees apply.

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