Five ways to become more data-centric

The ability to parse data – turning the numbers into knowledge – is a tremendous opportunity for organisations and the finance professionals who work for them.

That’s one key takeaway from a new CGMA report, From Insight to Impact: Unlocking Opportunities in Big Data. The report uses data from a CGMA survey of nearly 2,100 finance professionals, as well as from other sources, to outline the opportunities and challenges that organisations face in attempting to harness their data.

Companies are now collecting information on many fronts – including tracking the time it takes to serve a customer, weather and its effect on business, and the number of mentions on social media. How organisations apply the data to business decision-making can go a long way to determining how successful those companies are in the digital age.

The report offers five steps to creating a data-centric business:

1. Ensure you understand which new data would be relevant to your business model and competitive position.

  • Set out the business model and the intangible assets of your business. In particular, segment the main sources of income (by customers, channels or products) and the costs attributable to each (eg, logistics, operations, promotions, etc.).
  • Identify the data needed to describe and understand the drivers of these income sources and costs.
  • Consider what you would need to understand better to improve business performance overall.

2. Assess which data initiatives are already in place within your business.

  • Check which data platforms and initiatives are already in place within your organisation and which data are already captured and/or analysed.
  • Assess the speed and degree to which you can provide driver-based forecasting or dimensional analysis of business performance; this may be in the area of business data and not require advanced analytics.
  • Explore which external sources of data are potentially available for consideration.

3. Identify potential quick wins or small-scale proof of concept projects.

  • Assemble a team of enthusiastic people from different disciplines with the appropriate skills (IT, analysis, finance, business, etc.), backed by a high-level commercial champion.
  • Working with a small sub-set of the data available, demonstrate how insights could be derived and what value these could be to the business.

4. Conduct a formal data project to develop a related strategy.

  • Set out a full-scale data project, which will collect and analyse data and apply the resulting insights.
  • Identify the technology, skills and structure required to make the strategy successful.
  • Develop a business case.

5. Build on this initiative to start developing a data culture.

  • Ensure that data is regarded as an asset of the business as a whole. There has to be a joined-up approach between departments and a companywide commitment to assure good data quality across the enterprise.
  • Question internal assumptions, with a view to making it the norm to ask for the evidence to support any views expressed. Assist with the due diligence to verify any related claims.
  • Encourage innovation on data within the business, such as testing new data sources to explore alternative insights.
  • Tolerate failure. Where evidence emerges that a previously held view was wrong, ensure that those with an emotional investment in the position do not have a disincentive to accept the new insight.
  • Remember that data are often sensitive and valuable. It is important to respect confidentiality and apply the highest standards of business ethics and governance in the way data are handled.

Among the key findings in the report:

  • Firms face a steep learning curve in harnessing data for commercial benefit. Full adaptation to the data-driven era has been somewhat slow, as 86% of survey respondents say their businesses are struggling to get valuable insight from data. Before selecting a technical solution to pull data, companies must determine how they will use the information.
  • Finance professionals are well-placed to help translate data into commercial insight and value. More than 90% of respondents agree that finance can play a critical role in helping companies benefit from data-related projects, but there is uncertainty about exactly what that role might be.
  • Delivering on the potential of Big Data will make partnering between finance and business more important. Management accountants will need to partner with three sets of stakeholders: IT, data scientists and business leaders.
  • Delivering on new data insights is as much an opportunity for small and mid-size companies as it is for large ones. Almost two-thirds of respondents (65%) from smaller and mid-size organisations said they rely more on intuition and experience than on data analysis when making strategic decisions versus 47% of respondents from larger organisations. Smaller companies can benefit, even if they don’t have a large budget for data projects. The key to success is developing clear objectives for those projects.
  • Data hold opportunities for finance professionals to unlock new career opportunities. A strong majority (85%) said in the survey that the “data-enabled era creates an opportunity for today’s management accountants to develop new skills and competencies.”

Related CGMA Magazine content:

Three Reasons Finance Should Focus More on Business Intelligence”: The finance function is well-positioned to take the lead in helping businesses harness the power of business intelligence. Donny Shimamoto, CPA/CITP, CGMA, breaks down the reasons finance should jump at the chance to learn more about business intelligence.

Three Lessons in Managing Supply-Chain Data”: Aidan Goddard, FCMA, CGMA, the CFO and COO of L’Occitane en Provence’s Asia-Pacific operations, explains how Big Data, when harnessed, can help a company cut costs and inform sales and marketing strategies, and how finance figures in.

Six Key Components of Analytics-Based Performance Management”: When business analytics are applied to intelligence within an organisation, deep insight and foresight is produced.

Neil Amato ( is a CGMA Magazine senior editor.