Deciding which data to capture

Your first consideration towards data analysis should be to think about what type of data you wish to analyse and how you can best capture it from the wider business and beyond.

During this video extract from an FP&A workshop, experienced CFO and CEO Stuart Trood provides insights into how finance teams can determine what data to include and different ways to capture it:

Modern-day finance functions are handling huge amounts of data, including both financial and non-financial.  In many instances, your stakeholders will consider the non-financial data to be as important, and potentially even more important than the financial information.

Finance leaders should start by holding discussions with your management team, Board and other stakeholders to identify how they could use data to deliver their objectives and to support decision-making.  Many finance teams tend to reach their own conclusions about what data would be helpful to others and therefore other opportunities to add value to the wider business.

You may wish to adopt the following approach:

1. Define your target audience who you will be supporting through data analysis;
2. Hold discussions to understand what information would be helpful to them;
3. Ask them what format and level of detail they would like;
4. Determine where the underlying data is located; and
5. Implement systems and procedures to capture this information.

Finance leaders should determine how to capture data in the most efficient manner by integrating systems between your finance systems, other operating platforms used across the wider business and potentially external data sources for benchmarking purposes.

You will need to work closely with your IT and operations teams, plus you may benefit from seeking views from outside experts.

Regardless of your approach, you must ensure that the data is correct.  You will lose significant credibility if your data is inaccurate, no matter how well you analyse it!

Assess your skills

When did you last hold discussions with your target audience to check that you are providing them with the right data in the optimal format and at the right level of detail?

Have you considered whether there is anybody else who would benefit from your data analysis?

Could you improve the efficiency and format of how you capture data?

How confident are you that your data is 100% accurate?