Big Data – Cutting through the noise

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Big Data – Cutting through the noise

Big Data can deliver significant benefits, but senior finance leaders must invest in more than just the right technology to draw meaningful insights from it.

Finance chief are increasingly expected to help develop and define their organisation’s overall business strategy, something that is getting difficult to do without proper use of Big Data and data analytics. Indeed, 85% of companies surveyed by KPMG in 2016 said that delivering data and data analytics for business intelligence and management information is the greatest strategic value a CFO can bring to an organisation.

The big promise

Technology and analytics are hailed as the keys to unlocking the predictive potential of Big Data. Specialist analytic software vendors offer purpose-built tools that promise to uncover and interpret latent patterns, and generate “actionable insights” from the petabytes of information some big businesses now generate. These insights will then lead to cost and risk reduction, improved performance and efficiencies, new investment opportunities and revenue growth. They will also provide a better grip on shifting customer behaviours and, therefore, help predict future sales, cash flows and profits.

Pitfalls

In a rush to derive such value from Big Data, many finance leaders get a go-ahead for an investment in expensive data infrastructure and complex technologies. But these initiatives often lead to analysis for the sake of analysis and the organisation ends up with a handful of new metrics and dashboards that aren’t necessarily meaningful, let alone useful.

The 2017 survey by CFO magazine shows that 43.7% of finance functions do not have a highly effective data analytics program. Many deploy data analytics without first coming up with a defined and highly focused objective in mind, gathering irrelevant data or “getting bogged down in the details of the data and taking too long to make a decision based on [that] data.”

Others are unsuccessful because they apply new technology to “old paradigms” and produce “old school’” operations reports that analyse and report historical performance and trends rather than provide predictive insight to guide future decision-making. Some roll out the new systems “without a good understanding of the overall business needs and [with] lack of integration,” which leads to “spending too much time aligning and linking data, instead of working on the insights.”

Actions

Clearly, to extract value from Big Data, finance leaders need to invest in the right skills as well as the right technology.

A 2016 research study by Capgemini shows that 71% of finance functions have, at best, limited practical experience with Big Data and analytics, lacking the required skills and/or knowledge both in the technical domain and the analysis/statistical area.

The good news is that, according to the CFO’s survey, over 60% of CFOs and other finance executives plan to improve their own data analytics skills as well as the analytics skills of their existing finance team in the next 12 months. They will also require strong skills in this field from any new team members.

Finance chiefs must also systematically and regularly communicate Big Data insights to business leaders. Currently, the CFO’s survey shows that over 20% fail to do so.

Fortunately this is changing, especially in the sectors that are undergoing broader business transformations. According to a 2016 survey by EY, 67% of CFOs in the power and utilities industry spend more time today than five years ago on providing analysis and insight to support the CEO and senior leadership, as do over 50% of finance executives in cleantech, technology, diversified industrial products and consumer products sectors.

Wade Macdonald’s ‘Senior Finance Insights’ series aims to explore some of the real challenges and opportunities facing professionals in this space. Stay tuned for further insight.

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