The Art and Science of FP&A Storytelling

I recently participated in a web seminar on the Art and Science of FP&A Storytelling, hosted by the founder and CEO of FP&A Research Larysa Melnychuk along with other guests Pasquale della Puca, part of the global finance team at Beckman Coulter and Angelica Ancira, Global Digital Planning Lead at PepsiCo.

With advanced analytics, flexible dashboarding and effective data visualization, FP&A storytelling has become both an art and science.  You can watch the webinar here (registration required) to learn how to conduct FP&A storytelling in order to enhance fact-based decision making.

I’ve been working with planning and analytics teams for around 30 years, and my job was to talk about the technology aspects of storytelling, including the typical real-world barriers to success. You can find a blog post version of my commentary below, and a draft video of my section:

What’s new with analytics and storytelling for finance teams?

 Dashboards and analytics have been around for a long, long time. But recently, there has been a surge in demand.

Why?

  • First, because uncertainty exploded. Not just the pandemic, but also global trade tensions, Brexit in Europe, and things like the increasing frequency of extreme weather events. The rules of thumb and standard ways of doing business have been thrown out of the window. Business people want more data than ever.
  • Second, the stakes are higher than ever. We’re no longer talking about tinkering at the margins of a stable business model. It’s now about using data for survival in the present and new business models in the future.

This has lead to renewed interest in three areas in particular:

  • First, doing more with less. Organizations are interested in anything that can help, such as self-service, cloud, machine learning, and robotic process automation.
  • Second, getting a glimpse into the future. People really want to know what’s about to happen, so there’s lot of interest in leading indicators, scenario planning, and predictive technologies
  • And finally, agility. The only thing we can be certain about in the future is that it’s going to be different from what we expect today. So we have to be prepared to learn faster, and act faster than the competition.

What typically goes wrong?

I’ve worked with hundreds of dashboard and data visualization projects over the years. Here are some of the biggest technical barriers to success.

The first and most important is trust. The most powerful and attractive dashboard in the world is useless if the underlying data is inaccurate. Almost all the organizations I have worked with have systematically underestimated the time and effort needed to get good data, and to get people to believe that it’s good data.

Second, there’s nothing more frustrating than a visualization that indicates there’s a problem, but can’t explain why. People want to be able to drill from a high-level view down to the underlying business problem, without having to move to completely different systems.

Third, because everything is changing so fast, real-time access to data is more important than ever. Today, only 35% of organizations say their c-suite executives have access to real-time data. The power of cloud platforms and new in-memory systems are making this more achievable than ever.

Fourth, storyboarding – planning and analytics teams shouldn’t deliver just the figures. They should be “preinterpreted” and annotated to deliver the key insights to their business stakeholders in a way they can easily understand and act upon. It has to be simple and business-centric.

And finally, executives want to be able to compare what-if scenarios in order to make the best decisions.

Real-world storytelling dashboard examples

SAP uses our own dashboarding technology to access real-time data across all of our systems. There’s storyboarding, and it’s used directly in board meetings instead of powerpoint slides. For example, it’s used for pipeline forecasting, and it has been particularly useful recently – we cancelled almost all staff travel and physical events, and the system was used to project the effects on profitability. It has full support for value drivers, what-if analysis, and scenario planning, in the cloud.

Ferrara candy used analytics and dashboards during a recent big acquisition and they were able to get all the information they needed to run the business in real-time, literally at their fingertips.

And dashboards have been used to help organizations and countries cope with the pandemic. For example the busiest emergency department in the US used a cloud-based dashboard to quickly bring together data from multiple systems to get the insights they need for literally life-saving decisions.

The new exciting opportunities for data-driven storytelling

And now there are some new exciting opportunities, with AI-driven analytics and planning – fully 37% of organizations are planning to implement this within the next couple of years.

For example, we can give business people the ability to ask questions using natural language: “show me the budget vs actuals — by region, or by product, or business unit”

And we can use AI to do some of the data crunching for us – automatically spotting anomalies and outliers, determining the primary influencers on key indicators, and helping guide our analysis.

And I’m seeing massive interest in all kinds of predictive planning. The ability to easily create a predictive forecast from your planning model, and then inject the results directly into your projections is incredibly useful. Not just for expense and cost planning, but also revenue and sales planning, headcount planning, etc.

Practical recommendations for storytelling success

Ultimately, though, success with dashboards and data storytelling isn’t about technology.

It’s fundamentally about people, about your information culture. Inertia is a huge problem. People cling to the old ways of looking at numbers even when shown something better. Managers have to send a clear top-down signal that only data from the system will be accepted for decision-making.

In particular, a lot of problems happen when the indicators start to flash red—in some organizations, the dashboards are used as a bat to assign blame, rather than as a tool to come up with constructive solutions, and people spent time optimizing their excuses rather than fixing the underlying problems (and the whole notion of analytics becomes tainted and distrusted).

In general, I find people don’t spend enough time thinking through these people problems in advance—they treat it as a technology exercise rather than realizing that it really does impact company processes, teams, and individuals.

And too many dashboards are built to “show everything”. Lots of effort needs to go into making sure that those indicators really are actionable: What would “too high” be for that indicator? What would you do about it?

And finally, I see a lot of brittleness in dashboarding and data visualization projects. Executive sponsors leave, and the new executive wants to see a different set of indicators in a different format or in a different tool, and everything cycles around again. There has to be broad consensus around the KPIs, and flexible technology to be able to adapt to change.

The key takeaways

As I’ve said, data storytelling isn’t fundamentally about technology. But technology can help! Investments in data quality and automation, in particular, can go a long way towards getting a solid, trusted information foundation in place, so that you can free up time and effort for more strategic activities, and concentrate on getting the most out of your most important technology of all: people. The most important thing in business is… understanding what’s important!. Data can help with insights, but only people can turn data into innovation. (And, of course, at SAP, we’d love to help. 🙂)

 

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