Your Finance Digital Transformation Roadmap: A 2024 Expert Guide
Over the last few years, finance as a function has evolved and been reshaped by a number of digital transformations.
A couple of weeks ago, I overheard someone at a conference describe finance’s digital transformation as the equivalent of “sex in high school”; everyone is talking about it, few people are actually doing it, and almost no one is doing it correctly.
In my FP&A and finance transformation journey, I have been empowering finance professionals with data analytics, artificial intelligence (AI), and machine learning skills for the past six years. Over the last three, I’ve been deeply immersed in finance analytics and automation.
In that time, I’ve seen the powerful impact that digital transformation can have on the finance function. In response, I’ve created this roadmap for CFOs to be able to leverage the technological revolution, complete with key considerations and steps.
Let’s get started.
The Evolution Of Digital Transformation In Finance
Digital transformation within finance functions isn't a new concept. In fact, the way I see it, finance has been evolving in waves.
I’m willing to bet you don’t go a day in your work without looking at a spreadsheet… but before 1985? Maybe the super techy folks were using them.
Before we know it, we’re going to be saying the same thing about AI.
The common thread between them? The usage of technology to increase productivity and improve the outputs of our functions.
This year specifically, big names like OpenAI and ChatGPT have accelerated interest in AI from CFOs and finance professionals. You want to see how to leverage the power of this technology to improve processes, remove manual tasks, and increase productivity.
Which is why I’m glad you’re here.
These digital technologies are revolutionizing the finance function and, in particular, the roles of CFOs and FP&A professionals.
Robotic Process Automation (RPA)
It’s well know that in the world of finance and accounting, there are repetitive tasks that should be automated, currently requiring finance professionals to do them every day, week, month, or year.
This ranges from data entry to month end closes, from reporting on the last period to budgeting for the next.
The potential for technologies such as Robotic Process Automation (RPA), Microsoft Power Apps, or even Alteryx is immense here.
For instance, Alteryx is an easy to learn tool that has a “drag and drop” interface: finance professionals can extract data directly from ERP software, data lakes, or Excel files. Then, they can use pre-loaded automation flows to transform the data. This can be actions like automatically removing unnecessary columns, standardising file names according to your naming conventions, removing outliers or missing data, and more.
Finally, this tool also allows you to do data analysis on your cleaned data, then to load it to another tool such as Power BI or Tableau for visualization.
This process is commonly known as ETL: Extract, Transform, Load.
If your company is using Microsoft products, Power Apps can similarly empower you to automate previously manual processes.
Enhancing Finance Analytics
On top of automation, there are other data analytics techniques that are needed and useful for a successful finance digital transformation.
There are 4 levels of data analytics: descriptive, diagnostic, predictive, and prescriptive analytics.
Descriptive Analytics
On the first level, you have descriptive analytics: these allow finance professionals and teams to observe business processes and report what’s happening.
While these are the most basic level of analytics, companies normally spend most of their time here.
Think about presentations where people simply describe what happened: maybe net sales value (NSV) by category went down, or the cost of goods sold (COGS) went up. While it’s good to know these things, you need to go deeper.
Diagnostic Analytics
The second level is diagnostic analytics, which is where we get to the why. Rather than simply explaining what happened, we diagnose the change and understand why it happened.
Following our first example, this is where finance teams will mention that NSV dropped in Category A because of price or that COGS increased due to inflation in “X’ raw material.
This level is better than the first one because finance teams are spending time and understanding the root cause of the results. However, there are two more levels.
Predictive Analytics
Going three levels deep, you have predictive analytics.
In this level, the idea is to predict what will happen in the future. Many organizations are doing this through financial forecasting, either manually or with forecasting software. However, understanding whether a company is actually doing a successful finance digital transformation or not ultimately depends on the level of detail included in these forecasts.
There are many levers possible in a forecast and, if you don’t look at the right data, you won’t understand which levers are making the change happen.
Imagine that you sell bottled water. You just switched to a different packaging and sales skyrocketed. Great, right?
Maybe. What if I told you that at the same time as your packaging change, a massive heat wave rolled through? While pretty obviously the cause of the increased sales, if you didn’t include this data, you’d arrive at the wrong result.
Prescriptive Analytics
The fourth level, prescriptive analytics, is what’s going to set you up for financial transformation.
This level is all about using the data to support decisions on how to make a change happen, utilizing past data to inform you.
Prescriptive analytics would be the finance team suggesting that you enter a new market based on the data available, then having the NSV increase by 10% as a result of that decision. By getting into prescriptive analytics, you can transform your role from “bean-counter” to Oracle of Delphi.
So, how do you ensure you’re focusing on prescriptive analytics? By getting your tools in order.
Best Tools For Digital Transformation
Finance teams can focus on leveraging Python, R, Power BI, and Tableau to gain deeper insights into their data and unlock efficiencies in all 4 aforementioned levels of analytics.
Python and R
I know, I know, Python and R aren’t software tools but they are tools, nonetheless.
Until a few years ago, these languages were reserved for data scientists, statisticians, and IT. However, the democratization of knowledge and accessibility to them has increased. After all, Python is even available as an Excel function!
These powerful data analytics languages can change the way you look at data, allowing you to build (informed) predictive models, perform time-series analyses, and conduct financial simulations. Plus, they contain a huge array of libraries and packages specifically designed for finance analytics.
By leveraging AI and machine learning alongside these tools, you can make more accurate forecasts and data-driven decisions.
Tableau and Power BI
Tableau and Power BI are business intelligence tools. They have immense potential but most finance teams think their use case is simply making data look pretty.
These tools can play an important role in democratizing data, allowing a broader audience in your organization to understand the why behind the decisions that are being made.
The tools have features like self-service analytics, so even finance professionals with limited technical skills can explore data and generate their own reports, reducing the burden on IT departments.
Moreover, Tableau and Power BI support real-time data updates, ensuring that decision-makers always have access to the most current financial information. This real-time visibility is crucial for agile decision-making, especially in fast-paced industries.
The Future Of Digital Transformation In Financial Services
As we move forward, it's essential for CFOs and finance professionals to embrace these digital technologies. Regardless of whether you work in “fintech” or not, you need to continue exploring innovative ways to leverage financial tech.
While digital transformation may seem like a trend that’ll pass, I firmly believe it’s here to stay. It’s a fundamental change that will continue to change finance as we know it, on a global level.
It's a question of which side you and your organization want to be on: the side harnessing new digital technologies’ power and shaping the future of finance, or the side that’s comfortable staying where you are.
Recently, I was chatting at a conference with some other finance leaders and the parallel between current technological advancements and the introduction of Excel came up.
When Excel was new, there were some finance professionals that chose not to embrace Excel, preferring to stay with their “status quo” methods of using a calculator, pen, and paper.
They didn’t embrace change.
And in a few years’ time, they were completely replaced by people that did.
The finance teams that embraced this new technology re-shaped the way we looked at data, what we can get done, and finance as a whole function.
Now, I believe we’re looking at another “nexus event” that can re-shape our function.
So, how can finance professionals and organizations adapt to this monumental change?
Continuous Development Programs
To ensure that finance teams are well-equipped for the digital future, enterprises should establish ongoing training and development programs. These programs need to be designed to help finance professionals become empowered with the knowledge and skills needed to navigate the digital landscape effectively.
Hands-on training, workshops, and access to cutting-edge resources are essential components of these initiatives.
Practical Learning Experiences
Finance professionals need to get the opportunity to engage with digital tools and platforms and be coached on how to use them.
Many finance teams think that they don’t have time to learn a new software or a new way of doing things.
They think that finishing that one report or making sure that month end close goes smoothly is more important than doing a course on Power BI, for example.
It is up to us, finance leadership, to convince them that they have to make time for learning. If you learn how to automate a process or implement a new tool today, which could save you thousands of dollars and hours later, you’d be crazy not to.
It’s all about the “snowball effect” of learning.
Encouraging a culture of continuous learning and providing access to resources such as online courses and webinars can be highly effective in fostering this empowerment. And, most importantly, these learnings need to be practical! The days of expecting someone to complete a 20 hour online course or read a whole book about the application of Python are gone.
Like any busy student, finance teams need to be able to visualize the outcome of the technology they’re learning in order to justify spending time on it. This can be done by incorporating practical projects within your business, or within the courses, so that your employees start implementing what they’ve learned from day one.
This practical application not only solidifies their understanding but also adds tangible value to your organization's digital transformation journey.
Focus Groups and Proof of Concept (PoC)
Lastly, finance leaders also need to understand the power of PoCs. When rolling out digital transformation tools and solutions across the entire organization, it's better to start with focus groups and proof of concept projects. Treat every initiative as a new business; don’t start investing all your time and money into it until there’s some sign that it’s going to work.
Not only does it allow refinement before it’s rolled out, this is also a best practice in terms of change management. Iif a PoC works in a certain business unit (BU), implementing it in another becomes easier, as those that are confused can talk to members of the first one to get direction and hear the positive associations. While this can’t guarantee everyone will love the change, it sure helps.
7 Mistakes Finance Teams Make
Like any significant change initiative, there are some common mistakes within implementation.
Ensure you’re guarding against these things, so you don’t make the same slip-ups.
1. Lack of Clear Strategy, Roadmap, and Goals
The first common mistake is embarking on a digital transformation journey without a clear strategy, roadmap, or well-defined goals. Organizations can rush into adopting new technologies without fully understanding how they align with their business objectives.
To avoid this mistake, start by developing a comprehensive digital strategy that outlines the specific goals and outcomes you aim to achieve through your digital transformation. Though it may seem obvious, you’d be surprised at how many people charge forward without seeking clarity first.
2. Resistance to Change
People are stubborn; that’s unavoidable. However, your job is to understand that your team members may be resisting new technologies and processes due to fear of job displacement or unfamiliarity.
In order to overcome this, you need clear communication. Ensure that affected parties understand the benefits of digital transformation, provide training and support for the tools you introduce, and create a culture that embraces change as a constant.
Resistance to change may be commonplace but it’s also a great way to create a stagnant business.
3. Neglecting Cybersecurity
Many companies rush to adopt digital tools and platforms, neglect cybersecurity in the process. This can lead to data breaches and financial losses.
As the company’s financial leader, you need to prioritize cybersecurity from the beginning by investing in robust security measures, educating employees on cybersecurity best practices, and conducting regular security audits.
4. Overlooking Data Governance
In my opinion, this is one of the most critical errors people make.
It might not be the sexiest topic, but is one that us, as finance leaders, must understand and implement.
Data is at the heart of finance, and the mishandling of data can be a critical mistake within digital transformations.
Imagine implementing a $4 million business intelligence tool and then, when you open a report, the data isn’t correct! Not only would you lose the confidence of anyone using it, you’d be losing time and money for the business, too.
You must start by implementing a robust data governance framework: Define data ownership, quality standards, and data lifecycle management processes.
5. Poor Vendor Management
As a whole, vendor management is very important. There are many providers with tools that do the same thing, eager for your money, so you need to understand what’s out there before committing to a specific one.
Conduct extensive research upfront and you’ll save yourself any buyer’s remorse that may come.
For example, many finance leaders think that Power Bi and Tableau do different things and often they engage with both. In reality, these 2 tools are like Pepsi and Coca-Cola: The flavor’s a little different but if you’re wanting a drink, you’d only buy one of them.
6. Not Prioritizing User Experience (UX)
UX is often underestimated in digital transformation efforts. Teams can hire hundreds of software developers, without any UX Designers.
To understand the power of a good UX, think about ChatGPT. Yes, the technology is impressive but the real reason the whole world is talking about it - and not all the other chatbots and AI models - is due to GPT’s easy-to-use interface.
If you neglect the user experience in your digital transformation, chances are that you’ll be seeing low adoption rates and decreased productivity.
7. Failure to Measure ROI
Without proper metrics and Key Performance Indicators (KPIs), it's challenging to measure the return on investment (ROI) of digital transformation initiatives.
At the beginning, you must establish clear KPIs and regularly evaluate and report on the ROI of each digital project. From here, you can clearly see what’s working and adjust your strategy based on data-driven insights.
The Revolution Has Already Begun
Digital transformation is a process that has been ongoing for many years, gradually altering the way businesses operate across all industries; however, we’re now seeing technology emerge that could change the finance function more in 5 years than it’s changed in the last 50.
But I want to leave this on a final, important note:
In order to complete a successful digital transformation in your businesses, you need to be mindful of 3 main things: People, Process, and Technology.
Many companies think that Tech is the only important thing, especially now that digital technologies are revolutionizing the finance function and, in particular, the roles of CFOs and FP&A professionals.
But without taking care of the people and process elements, digital transformations are doomed to fail.
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