Business reporting in a digital world has been saved
Business reporting in a digital world
The "Crunch time" series for CFOs
When you say the word reporting, binders full of spreadsheets, charts, and footnotes might come to mind. Or maybe conference rooms with executives grinding through slide presentations. And behind it all, there’s an army of Finance people who’ve been working for weeks to pull it all together. The ritual continues, month after month after month. In the best of all worlds, this ritual would deliver reports aligned with the changing needs of the business. That rarely seems to happen.
Spend too much time creating reports? There’s another way
In most companies, management reporting works like this: Finance determines what’s important for various levels of management to see, and then pumps out that information to recipients on a regular basis. As new requests get added to the mix, the burden of internal reporting grows; rarely are reports removed. And through it all, Finance seems to have little visibility into how reports are actually used—or if they’re used at all.
So the main reason to think about improving internal management reporting is quality: The promise of better decisions.
External financial reporting is different. Much of the required content is driven by various accounting and regulatory bodies, so there’s not a lot of room to wiggle. For external reporting, improvement is mostly about efficiency, while maintaining accuracy and control.
The good news? The benefits of both reporting quality and efficiency can be delivered by the same set of digital technologies—at a substantially lower cost.
The future of business reporting
What will reporting look like in five years? More specifically, what will we actually see on the ground in leading finance organizations around the world? The laborious grind of management and financial reporting today won’t exist in the future. People will be insight generators, not report builders. The talent pool in Finance will expand to include business people with finance backgrounds, data scientists, and storytellers—all collectively enhancing Finance’s ability to support the strategy of the company. In addition, we see three key characteristics transforming how reporting will get done in the future. Reporting will be intelligent, interactive, and real-time.
Potential benefits of transformed business reporting
- Lower cost
The savings companies can see as reporting evolves will be real and sustainable. Companies will be reducing human labor significantly – and delivering reports vastly more efficiently.
- More insights; fewer manual tasks
The potential for value creation from improved reporting is even more promising. Finance is supposed to help the business uncover insights. That can’t happen when people are bogged down with spreadsheet farming, reconciling data between systems, or assembling massive binders.
- Improved decision making
How many leaders served by Finance will stand up and say that Finance has had a significant and consistent impact on the quality of their decision-making? That’s hard to find today, but it’s much more likely tomorrow.
Much of reporting in the past has been defined by the steps required to produce the reports themselves: collecting data, constructing reports, and disseminating them. That’s changing. In a digital world, dashboards and digital technology do a lot of that work, which means humans get to do more interesting things.
Digital technologies driving the future of reporting
A handful of digital technologies are coming together to reshape how companies can do reporting. We’re seeing the early signs of all these technologies being adopted.
|Robotic process automation
RPA software shortens the time companies spend on data manipulation by automating routine tasks.
These dedicated virtual assistants enable users to interact directly with data using voice or text queries.
These now familiar tools allow people to display and play with data dynamically, so it’s easier to understand and interact with.
This collection of technologies includes natural language tools that can read and write, as well as machine learning.
This statistical technique uses algorithms to execute forward-looking analysis – especially routine financial forecasts.