Introduction

Following on from part one, the Finance Tech Stack Roadmap, it’s important that we understand the journey we need to take our finance teams on. 

It’s equally important to have some guiding principles we can use when we start to get a little more granular in our roadmap and start to assess different pathways.

Some pathways are not about technology at all but simply culture and mindset. 

But there will come a time to invest in the enablement environment through technology. 

There is so much on offer but understanding the technology can be challenging for the average finance professional. 

The overwhelming use of jargon (AI, RPA, XFPA etc) and terminologies often confuse solutions and blur the lines that mask the real problems.

What are the real problems?

There are many problems with the status quo, but some of those are perpetuated by the industry that tries to solve the same problems.

Promises are made relating to technology that fails to deliver the results guaranteed by the vendor sales team. 

Outlandish claims of removing Excel (whilst their software looks like Excel) and pitching business intelligence solutions that are in many cases sub-standard when compared to leading BI tools like PowerBI or Tableau.

Educating our teams on when they should look beyond just Excel (cost-effectively) is not even discussed, but should be the first thing we teach them. 

So how do we get started then?

It’s time we arm our finance teams with some fundamental principles and focus areas to enable them to really find the best technology solutions that solve real business problems, not just symptoms of bad spreadsheet habits.

Let’s not throw the baby out with the bathwater, but find ways for the baby to swim in a bigger spa bath with bubbles.

The lack of integration between finance and sales & operations (S&OP) systems often leads to “Excel middleware” being used which only increases the risk. 

Whilst killing the spreadsheet is also often seen as a way to stop the risk of errors however many are not aware of the data wrangling tools inside Excel-like PowerQuery. 

Removing the spreadsheet does not solve the right problem. The problem is not the spreadsheet (or any tech for that matter) but the way our teams are using it.

So we start the journey with awareness and educating our teams on the principles to consider whether wanting to solve problems using technology.

Let’s get to those principles


Having researched this space deeply I wanted to share these principles and questions, which I ask when assessing any new “tool”. 

We never stop looking at new tools for financial modelling and analytics. 

We love shiny toys (who doesn’t), but this can also waste a lot of time and increase risk if you are not careful. 

Deciding NOT to use a tool is as important as a decision TO use it. 

But sticking with native tools built by a particular vendor that doesn’t have the ability to evolve with changing business conditions is equally problematic. Some examples of the added flexibility some tool have today include

Excel with Addins (PowerQuery first came to Excel as an add-in)

PowerBI with the App source

iPhone (IOS) with the App Store

Android phone with Google Play

Why do you download apps to your phone, yet your native work tools are kept in their original native state? 

Maybe it's time to explore the world out there (carefully) using these principles which have guided us through many different tools.

Principle #1 - Scalable content 

What content does your solution contain? 

Can you scale that content easily across products, business units, companies etc

Is it capable of connecting the content between the finance, sales and operations teams? 

What about strategic decision making and scenarios across the organisation? 

By ensuring you have the ability to search for broader insights beyond just the general ledger is vital. 

Where financial information is available, does this content consider all three financial statements?

The Income Statement, Balance Sheet and Cash Flow Statements for Historical and Forecast financial information is critical for better modelling. 

But more important is the ability to forecast the balance sheet including key assets and liabilities that impact the most important asset, cash! 

Principle #2 - Flexibility

Does your tech allow the mere mortal human to adapt it to your specific business processes, logic and ever-changing needs? 

In other words, are you able to customise it without much effort, or are you about to sign a contract that makes someone else very wealthy and you a slave to their consultants? 

If you want to change key strategic and structural decisions easily are you able to?

The ability to change and adapt is the hidden costs many fail or see or consider as you cannot see into the future. 

But if there is one thing that you can absolutely guarantee will happen, it’s change. You may not know when and what, but it is inevitable. At some point in the future what you build today will become redundant or less relevant unless it is flexible.

Principle #3 - Driver of business decisions and performance

 At times systems are being upgraded and maintained just to keep the lights on ie not really upgrading the capability given the difficulties in justifying the big cost for those add-ons, versus creating your own. 

Often those expensive add-ons are purchased and left to gather dust as nobody knows how to use it internally, and are afraid to admit it.

If the technology is not assisting in driving or supporting business decisions then why bother?

Would you invest in this tool if it was your own money and how would you recoup your investment?

Driving business decisions and impact means you need to track rolling actual data and KPIs that can be compared to a target. 

If you are not tracking progress and aiming for success you simply will never get it. 

What if you need to quickly run live business scenarios and sensitivities to explore an idea or sudden change in the business trading environment. Can you drive your performance culture despite these changes?

Principle #4 - Time saver

How much time will you really save and how quickly will it be realised? 

How much time and effort will it take to get set up?

Is it going to make your monthly reporting processes quicker and easier especially when the chart of account changes or you need to change the way the business calculates its revenue? 

Is there an API that can update the data live when you need it or do you need to put a spreadsheet middleware solution?

If you are not thinking about time from an end-to-end context you can be a little horrified when you discover that the new system can absorb more time in areas that you had not considered before. 

Especially for your finance teams.

Principle #5 - Total Cost of Ownership

What is the annual licensing cost and what costs are hidden eg Adhoc or technical support? 

What about the cost of upgrades?

Many ERP users are being stung with a massive end of life (cliff effect) upgrade cost. Forcing many to invest millions just to prevent the system from being unsupported. 

What about the often hidden internal IT support costs? 

Will you need more IT staff to support this new system with specialist skills?

If you are an SME are you charged on a per staff user basis or on a per-client basis if you are using some cloud accounting apps? 

In other words, does it cost you more the more clients you have and will your clients also need a license to use it?

The cost equation is critical to understand whether you are scaling your business or someone else's?

Principle #6 - Training

What is the cost and quality of the training? 

Is it available online and face to face? 

Will it remain available for the team to go at their own pace? 

Are there YouTube videos and similar content available for them to learn and share knowledge with other users?

Does it contain a public knowledge bank or wiki?

Not having access to training or public forums means troubleshooting and problem solving is often a costly exercise. 

How many people use the system and can therefore support each other without the hefty cost each time?

Perhaps just Google something relating to the software and see what you find?

Principle #7 - Control

Does the system ensure you have accurate financial information securely? 

Can you set up different access levels including row/data or object-level security features? 

Giving everyone access to payroll information is probably not ideal.

What level of data protection exists and has the software been penetration tested? 

Allowing users access to be customised and controlled can avoid problems down the track.

Principal #8 - Ease of use

Excel, when used properly, is still the most ubiquitous solution. 

It’s this ease of use across many people that results in it becoming a default Swiss army knife of business tools.  

When considering a solution will it become “Excel-like” for broad-based adoption because it’s easy to use or will it gather expensive dust? 

 Can other people use it (not only internal staff), perhaps a 3rd party e.g. a bank without also having to purchase the license? 

Can you send it to someone to operate easily for example running scenarios or sensitivities?

Enabling many people to use it easily is a sure way to achieve the highest return on investment.

If people are not using it, why is that? 

What will it take for greater adoption and has the vendor considered UI & UX principles deeply?

Applying design thinking principles is also key to successful adoption.

Principle #9 - Integration

Too often we see tools that have a very narrow focus and don’t allow or play well with other tools. 

This is particularly true when it comes to BI tools that bring data together from many different sources. 

Does the solution integrate easily with any other system outputs in universal formats like CSV, Excel or similar data sources? Ideally, this should be automated as much as possible. 

Is it possible to structure the data coming from that source into multiple drivers? 

In some cases, we often see the chart of account structure for one revenue account that captures multiple products and customers all at different prices.

How easily can you forecast based on drivers for strategic planning for product lines or new business locations, distribution channels or will this require additional configuration and more cost?

Conclusion

If you want to learn more and also understand how you can upskill in Financial Modelling and Analytics (FMA) be sure to reach out to us or stay tuned for more articles content on this important topic.

I encourage you to also take a peek at the past articles on financial modelling which is the foundation of business decision making, planning and forecasting.