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5 Ways to Boost Your FP&A Skills and Improve Your Analytics

  • By Pramod Kumar Bagri
  • Published: 6/30/2015

Whether you get bogged down in routine or a part of a large department, sometimes it’s hard for financial planning and analysis professionals to stand out. Here are five ways to gain your manager’s attention—and help your organization.

Introduce visualization charts for descriptive analytics that you drive. For instance, instead of showing how each region has contributed to your sales of $100, consider pulling up a simple “waterfall” to show. You can quickly learn how to create a waterfall in Excel just by performing a web search; a myriad of resources will appear. You can use a waterfall to explain the variances or any other factor that moves from one position to another.

  • You are doing fine if you can identify areas you can chart out.
  • You are doing very well if you can start putting things on the chart.
  • You are doing great if you can bring in visualization software like Tableau, Qlikview, etc.

Find the major components of your revenue or costs and see if you can find the driver and start tracking it. For instance, if you have just been reporting sales, start seeing if you can report number of units and price. Track changes in revenue driven by units and by price. See if you can bring in macro lever to measure. See if you can bring in industry specific levers. For instance, if you are in the energy industry can you connect price with GRM? Do similar things for all important elements of you costs. Start with something and keep moving towards all revenues and costs till it covers 80 percent of your bucket.

  • You are doing fine if you can identify levers for the line items.
  • You are doing very well if you can start reporting by levers impacting rather than at line item level.
  • You are doing great if you can bring in industry flavor.

Try to pull up basic statistics and summarize the information you have. This can be done in a very simple way using Excel data analysis.

  • You are doing fine if you can start reporting the statistics.
  • You are doing very well if you can compare this across time periods/segments.
  • You are doing great if you can have commentary on the variances.

If you are forecasting, find areas to start using data science on places which has maximum impact on your forecasts.   

  1. Map the volume/quantum/dependency of an item.
  2. Map the error rate in the past. This can be done by mapping your forecast number against the actual for past six months.
  3. Map the ease of getting data.

Put on a simple bubble chart with error rate on the x-axis, ease of getting data on the y-axis, and size of bubble represented by volume.

Involve your organization’s data scientists to figure out if you can apply regression techniques, time series techniques for forecasting to validate the “gut feel” number with the “data backed” number. There is a good chance it will bring in more accuracy with lesser effort

  • You are doing fine if you can understand one item you can start forecasting with data science.
  • You are doing very well if the data scientists can learn these techniques.
  • You are doing great if the data scientists can model things out.

Map the areas where management constantly reaches out to the team for decision support system. Involve the data scientists to check if you can apply simple linear programming to find a data-backed optimization model. Instead of allocating marketing costs by last-year allocation, see if you can use linear programming to allocate marketing costs to maximize the penetration.

  • You are doing fine if you can understand the area constantly requested by management.
  • You are doing very well if your data scientists can learn the basics on linear regression.
  • You are doing great if your data scientists can optimize with linear programming.

Note that for the last two tips I have said to involve data scientists; I did not introduce him/her to you. That’s because you are that data scientist. None of the techniques I listed are rocket science. There is loads of material available in YouTube, Coursera and the like to help you improve your FP&A skills and become a data scientist. Just spend some time to start knowing basics of it. Get your hands dirty. If you want to move up the ladder remember the expectation from the FP&A lead has changed.

Pramod Kumar Bagri is AVP, Finance Analytics, Accenture in Bengaluru, Karnataka, India.
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