You do not have to be a data scientist to recognize the impact of technology on FP&A is and will continue to be significant. If you are still skeptical, have a look at a few blogs written by Lance Rubin where he disrupted his own role.
One of the biggest challenges of automation (Robotic Process Automation) and artificial intelligence/machine learning technologies is our current mindset. It is critical for success in our careers and the companies where we aim to drive the right strategic choices. However, with so many new acronyms and complex terms, it’s proving difficult for us to get comfortable with it and the mindset shift appears somewhat crippling. It doesn’t have to be. To tackle this and help you gain some insight we assess this by adopting the four attributes of curiosity, courage, crystal ball, and clarity which was defined in the previous post, “Why Transforming Your FP&A Matters,” as attributes critical to the future success of FP&A.
Spark new found curiosity on how much of the boring stuff can be automated, giving us more time to build relationships, find value creating opportunities and listen to our key stakeholders.
It will no doubt take a huge dose of courage to not only start, but execute on the transformation. These are often not “out of the box” solutions and will require us to spend time learning new skills in process automation, analytics and financial modeling. We don’t need to know exactly how to do it for all of these but at least understand how they work, where they can add value and where they won’t.
AI-based machine learning and predictive analytics will start to give us more powerful crystal balls. This is a space that is largely unexplored and represents immense potential for us to understand, interpret, communicate and execute on these predictions. At times even call out when they might be wrong (which won’t be often but can still happen.)
Technology will help guide our roles more clearly over time and the mindset shift will hopefully become more tangible and easy to absorb.
Just as well as our mindset is on a journey, when it comes to understanding innovative technologies so is data. Data is travelling from sources to uses, with the hourglass as a metaphor of gathering vast amounts, processing and then disseminating.
Exploring the technology opportunities in FP&A
To further help you understand how technology will change FP&A let’s explore the art of the possible. Paresh Mistry has published a blog which provides a good framework as a starting point.
There is little argument that some of the leaders in cloud accounting tools are Xero and Intuits QuickBooks Online. The API (application protocol interface – how machines talk to each other) connected ecosystem of apps is a true game changer. Something the larger enterprise resource planning (ERP) systems can learn from with decentralized app development. Most ERPs are closed systems meaning they won’t necessarily suit everyone and as a result ERPs sometimes result in more spreadsheets, not less. The right ERP tool will help you evolve with the business, not create more challenges for you.
RPA (Robotic Process Automation)
It comes in many different shapes and sizes that range in complexity. I love the way Chris Argent explained RPA with micro and macro macros. There are a few out there:
Excel automation (micro macro tools)
The often-forgotten Excel macro, Excel add-ins offer a range of data importing, model building and automation of manual processes within Excel without coding, Excel’s own in-built tools for getting data like PowerQuery, PowerPivot and the ever-increasing functionality like dynamic arrays etc.
Cross system (macro macros)
Macro macros with cross system process automation. RPA is the enabler for creating more time to explore other technologies and free up substantial amounts of time that is needed to learn new skills. The spare capacity can also be used to focus on value-adding decision making tasks and therefore should be an opportunity, not a threat.
Firstly, it includes all forms of analytics which are heavily data-driven. Especially clean data or even enriched data which brings financial and non-financial information together can be powerful.
As the reliance on data-driven decisions becomes more prevalent in finance, there is a need to manage data better and remove data anomalies or errors in the “cleansing” process. The “dirty” data can cause false positives or other issues as a result of the data being incorrect, often caused by a human.
Once cleansed, its possible to enrich the data. For example a customer name and ID is not as valuable as the customer’s postal code, income bracket or other spending habits which could be enriched from data collected from Google for example. This enriched data can then inform the marketing team more specifically the personas and buying habits for their products and in order to achieve higher ROI from marketing spend. There are even some technologies which can extract insight from not so “clean” data to identify trends and anomalies.
The forms of analytics are typically descriptive, diagnostic, predictive and prescriptive, each of which have a focus either backward looking or forward looking and range in complexity as a result. These will certainly give you lots of insight and some very narrowly defined foresight, but unlikely to ever be widely defined 3-way predictions for Finance.
3-way predictions or forecasts typically include the Income Statement, Balance Sheets and Cash Flow Statements. These forecasts are more aligned to financial modeling, rather than analytics as they include the balance sheet positions, cash flows and profitability in an integrated manner. Analytics applications include data visualization tools as well as data ingesting capabilities across numerous sources from web pages to databases to core accounting systems.
Modeling can come in various forms including predictive modeling and data modeling mentioned above. Generally financial modeling is extensively used within Excel. Major investment banks and project and infrastructure finance but also for business in robust cash flow modeling. It’s possible to build models on other applications like Google Sheets etc., but these tend to be for simpler models.
It is a lot of information to take in, but simply showing you the art of the possible should prepare you for what’s coming. It should also help you formulate a plan for how you want to use technology in your FP&A transformation.
It’s not the technology
AI + Human > AI alone
While large parts of what we do today will change, most of what we are going to be doing in the future is still uncharted and more opportunities will be created as a result as we create innovative solutions by applying what’s often open source i.e. “free”. Only if we are open to them, though.
In the great words of Dr. Carol Dweck, “Yet.”
We might not be ready yet, but we certainly can be if we embrace the massive opportunity we have to leverage data, technology and value creation through softer skills such as influencing and storytelling. The technology is there and will only get better.
The longer we resist the more opportunities we miss out on.
Technology presents a massive opportunity for FP&A to enable the transformation that must happen. Excel is great if you know how to use it properly, yet the clear majority of us do not. Therefore, technology may provide you the boost you need to let go of low value-adding tasks and start driving the right strategic choices in the company.
What’s your approach to technology? We would love to hear about your successful technology adoptions and integrations! Are you strictly an Excel user or have you opted for a more modern tool?