How Technology Will Change FP&A Forever
If you are skeptical look at previous blogs written by Lance Rubin where he disrupted his own role.
But one of the biggest challenges of automation (RPA) and AI/machine learning technologies is our mindset. It is critical for the 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, but 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 mindset article as the critical attributes to future success of FP&A.
Curiosity
Sparks 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.
Courage
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”, “plug n play” 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.
Crystal ball
AI based machine learning and predictive analytics will start to give us more powerful crystal balls.
Adopting more advanced Monte Carlo simulation. 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).
Clarity
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.
More data is being created (IOT as an example) and captured (Cloud), and our ability to analyze it as humans is magnified by automation (RPA). We need the tools to keep up, but the tools also need us to be effective (Analytics). Goal is analytics to insight that can then be shared via any number of mechanisms (Mobile and Social being just examples).
Exploring the tech stack smorgasbord
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. Read more here.
As visualized above we’ll use the ICRAMS model (Internet of Things (I), Cloud (C), Robotic process automation (R), Analytics (A), Mobile (M) and Social (S)). ‘ICR’ acts as the enabler and sensors; ‘AMS’ is the feedback and decision-making engine.
Let’s focus on the ones that have had the biggest impact to date and proven business outcomes.
Cloud
No question the leaders in this SME space are Xero and Intuits QBO. The API (application protocol interface – how machines talk to each other) connected ecosystem of apps is a game changer.
Something the larger 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.
RPA
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 (VBA code based), Excel add-ins like Modano and DataDear for a range of data importing, model building and automation of manual processes within Excel without coding (managed Excel), Excel’s own in-built tools for getting data like PowerQuery, PowerPivot and the ever-increasing functionality like dynamic arrays etc. Excel enterprise management tools like Vena solutions for example which contain a range of other tools surrounding the Excel enterprise environment.
Cross system (macro macros)
Macro macros with cross system process automation like Automation Anywhere, Solvexia, Blue Prism, UiPath, Xceptor and Redwood.
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.
Analytics
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.
Technologies used in Analytics include applications like PowerBI, Tableau, Qlik, Domo and many more. The predictive and prescriptive aspects require the use of machine learning and other code-based languages like Python and R scripts.
The Analytics applications include data visualization tools as well as data ingesting capabilities across numerous sources from web pages to databases to core accounting systems.
Financial Modeling
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.
However, there are other powerful add-ins like Modano for building 3-way models quickly, DataDear for extracting and pushing data between the cloud package and spreadsheets and interactive modeling visualization of Modeler which also has 2-way data flows. The combination of these make it very powerful as well as visually appealing.
We know that is a lot to take in but simply showing you the art of the possible should prepare you for what’s coming your way. It should also help you formulate an ambition for how you want to use technology in your FP&A transformation.
It’s not the technology, stupid
AI + Human > AI alone.
This is a fact, so whilst 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 yet be ready, but we certainly can be if we embrace the massive opportunity we have, to leverage data, technology and value creation through softer skills of influencing and story-telling. The technology is there and will only get better. What matters is how we as humans adopt this technology and embed it into our way of working.
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 don’t. Therefore, technology might help give 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? Are you embracing everything that’s coming at you or taking a skeptical approach thinking what you have is just fine? We would love to hear about successful technology adoptions or even how you managed to boost your productivity by simply using Excel better so show us what you’ve got!
This article was co-written by Lance Rubin and Anders Liu-Lindberg. It forms part of a collaborative series of articles that draw on expertise from around the world to cover multiple crucial topics around the theme of the changing FP&A practices. Read the original and explore further into the series here.
