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Five steps to creating a data-centric business

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29th Oct 2013
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The volume and variety of data available for analysis by businesses is expanding exponentially, explains CIMA’s Peter Simons.

Meanwhile, increasingly powerful technologies have emerged to enable more sophisticated data management and analytics. These related trends, popularly summed up by the term ‘big data’, are combining to enable today’s organisations to unlock new sources of insight and value.

Inevitably, taking advantage of these opportunities with data will push accountancy professionals into new and unfamiliar areas, and require them to develop new skills and new ways of thinking.

For those who can manage that transition successfully, however, there are clear opportunities to play a decisive role in an area that will become an increasing source of competitive advantage for firms of all types and sizes in the coming years.

To make the most from these opportunities and start to create a data-centric business, finance professionals will need to heed the following five steps:

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

As a first port of call, set out the business model and the intangible assets of the business you work for. In particular, segment the main sources of income by customers, channels or products and the costs attributable to each such as logistics, operations and promotions. This will help you to identify the data needed to describe and understand the drivers of these income sources and costs, making it easier to see which areas you need to understand better.

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

Check which data platforms and initiatives are already in place within your organisation, and what data is already captured and/or analysed. Then, assess the speed and degree to which you would be able to provide driver-based forecasting or dimensional analysis of business performance. Once this is done, you can move on to explore what external sources of data are potentially available for consideration.

3. Assemble a team to help identify potential quick wins or small-scale proof of concept projects

To truly unlock the opportunities in big data, management accountants need to partner more closely with three sets of key stakeholders: Their colleagues in IT who capture much of the data; the data scientists who can perform advanced types of analysis on that data; and finally business leaders who can ensure new ideas are turned into concrete action. As such, assembling a varied team of enthusiastic people from different disciplines with the appropriate skills and backed by a high-level commercial champion, will be an essential part of the process.

This requires financial professionals to have a broader range of management skills: Clear communication, the ability to lead and influence, and a strategic understanding of the business – all of which are essential for the business partnering role that many firms want finance to play.

Working with a small sub-set of the data available, your assembled big data team can together 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 start to apply the resulting insights. By identifying the technology, skills and structure required to make the strategy successful you can help to develop your business case. What’s more, with these insights, companies make improvements to their core processes and business models which can often lead to substantial cost savings or new business opportunities.

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

Following the development of your data project, you can start helping data to be regarded as an asset of the business as a whole in several ways. First, be sure to create a joined up approach between departments, and make a companywide commitment to assuring good data quality across the enterprise. In a recent study CIMA conducted into big data, about half of finance professionals said they saw data quality as being a weak point in their organisation’s current skills to capture and extract valuable insights out of data, so the importance of this is huge.

However, it is also important to strike the right balance as finance professionals can tend to overemphasise the importance of data integrity, given how important this is for statutory reporting. In data exploration, by contrast, finding patterns or correlations to determine whether something is directionally correct may matter more than total accuracy.

On this note, remember that finance professionals need to be tolerant of failure: Where evidence emerges that a previously held view was wrong, you should ensure that those with an emotional investment in the position do not have a disincentive to accept the new insight. What’s more try to encourage innovation on data within the business, such as testing new data sources to explore alternative insights.

Lastly, data is often a sensitive and valuable asset so it’s always important to respect confidentiality and apply the highest standards of business ethics and governance in the way that it is handled.

Peter Simons is a technical specialist at the Chartered Institute of Management Accountants (CIMA).

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