Millennium

Delivering Finance Transformation: A pandemic shouldn’t mean pushing back

As of early 2021, the backdrop for a major finance office transformation project could hardly look more challenging. Organisations remain in recovery and stabilisation mode. Roles have been amalgamated, workforces are largely scattered and budgets are under pressure. So does this mean that transformation ambitions are being put on ice for the time being? Far from it.

According to Deloitte, 73% of organisations were using automation, machine learning and similar technologies at the end of last year, up from 58% prior to the pandemic. These capabilities certainly proved their worth, with two thirds (68%) of business leaders using automation to respond to the impact of Covid.

This is exactly the time when legacy systems and processes could benefit from an injection of efficiency. But if the finance department is grappling with organisational disruption, how do you go about getting your plans off the ground?

Here’s a closer look at the Covid-related barriers to finance transformation execution, and how to overcome them.

The Challenges

Competing Priorities

According to your original plans, 2020 may have been your year for overhauling outmoded finance processes and updating your reporting capabilities. However, once the pandemic arrived, priorities shifted. CFOs frequently take the strategic lead on transformation, with considerable input from IT. Inevitably though, IT departments suddenly found themselves having to devote time and resources to the rollout of technologies such as video conferencing, VPNs, laptops and printers for home use, as well as the provision of remote support. New tech for finance may have got pushed to the back of the queue.

By now, the initial technical set-up woes linked to the sudden shift to home working are largely behind us. But if IT is still focused on things like cloud architecture, the introduction of new collaboration software and enabling blended home/office working, it could be that the implementation of specialist finance technology remains pretty low down the priority list.

A reduced workforce

When the staffing budget is under pressure, the office of finance is not necessarily immune to cutbacks. And if team members are furloughed or let go, it usually means a larger workload for those remaining.

Against this background, the focus may very well be on keeping the lights on: i.e. while focusing on core tasks with a skeleton staff, the feeling is that there simply isn’t the bandwidth to devote to transformation projects.

Scattered employees

Typically, a finance transformation strategy covers a review of organisation-wide reporting processes, a review of your data sources and architecture and side-by-side analysis of possible new solutions to adopt. Next comes implementation, migration, training and optimisation. It’s a lot – and it usually involves multiple stakeholders from across the company.

Effective communication is key to the delivery of any project; especially if you have to coax busy people into action! In normal times, when everyone is in the same building, all of those ad-hoc mini-meetings and impromptu watercooler moments can actually go a long way in keeping things moving. If interaction is currently mostly limited to your morning Zoom meetings, it can be hard to build any kind of impetus.

The Solution: Getting Finance Transformation Back on Track

Restate the business case for transformation

You can characterise technologies as either ‘business critical’ or ‘nice to have’. And right now, many organisations are focusing solely on the former.

This is the time to restate the case for office of finance transformation, not as a luxury, but as something that’s absolutely critical to building business resilience. By way of illustration, here’s a rundown of what’s typically expected of the finance department in the current climate, and at how transformation projects can directly address these critical requirements:

We expect finance to ‘do more with less’. New capabilities such as automated close and consolidation, budgeting and forecasting will help reduce the huge amount of resources expended on routine tasks. Regardless of any staffing pressures you may be facing, your regulatory and compliance burden remains stubbornly real. Specialist solutions to address specific compliance issues (for instance, lease accounting and revenue received) will go a long way in helping you stay on top of your obligations.

We need finance to be more involved in strategy. Updating your reporting capabilities will reduce the time needed for manual-heavy tasks, freeing up time to devote to strategy. Also, for your input to be of real value, you are going to need the ability to track, measure and analyse key metrics and deliverables.

We need to predict future events and respond quicker to change. Volatility and unpredictability are likely to be permanent features on the landscape. When Gartner asked top CFOs to list their priorities for 2021, “Advanced data analytics technologies’ came top. To us, this comes as no surprise. Weathering the storm demands the ability to model for a range of scenarios, to analyse rapidly changing conditions in real or near-time, and to pivot quickly: something that’s very difficult if you are still struggling with Excel for modelling.

As a CFO, you may currently be experiencing board-level pushback to transformation due to budget restraints or staffing limitations. If so, it’s worth stressing that if the finance function is to deliver the type of business-critical insights expected of it, it is imperative that processes, workflows, reporting and analytics capabilities are rendered fit for purpose.

A new approach to management

With authorisation to proceed with your transformation strategy in place, it’s important to consider the practicalities of execution.

If you have led internal change projects in the past, bear in mind that this one may require a slightly different approach. Remote working means that short-notice, face-to-face roundtables may no longer be an option. The same goes for being able to pop your head around colleagues’ doors to check on progress.

Tip: in addition to regular video-con updates, where multiple stakeholders have designated tasks to complete in order to progress the project, a simple project management tool such as Trello can make all the difference in keeping matters on track.

Also, when it comes to actual implementation, beware of false assumptions on what is and isn’t possible remotely. You may be pleasantly surprised here. For instance, Millennium Consulting’s experts are routinely able to manage and execute all aspects of new finance technology implementation remotely. This includes scoping and planning, right through to migration, installs, configuration and training.

Filling in the skills gaps

Even in ‘normal’ times, managing and executing finance transformation is not easy. It demands expertise in data management and architecture, reporting best practice, an eye for the right technology to avoid making expensive mistakes, the know-how to configure it correctly and put it to work, together with project management experience to bring everything together.

The skillset may seem daunting: even more so if Covid-related budget restraints make it difficult to hire new talent. This is where external input can prove invaluable. Rather than the ‘hard sell’ on favoured technologies, or rigid, needlessly expensive support packages, what you really need is unbiased expert advice and targeted input to complement your own internal resources.

Ready to get your finance transformation project back on track? Speak to Millennium Consulting today.

AI replace human decision-making

AI delivers the full picture

What do customers really think about our brand? Where is the next big trend coming from? How can we tell when a client is about to leave for a competitor, or a piece of machinery is about to malfunction?

Conventional performance management solutions and other types of business software are fine for basic number crunching but isn’t always capable of answering these kinds of big questions.

Humans are much better at interpreting nuance. Trouble is, we cannot be expected to read absolutely everything that may be relevant to business decisions, and we can’t be on call 24/7.

An estimated 73% of company data goes unused for data analysis. Often, this is because certain datasets are too difficult to interpret: data is unstructured, or else there’s just too much of it.

AI happens to be extremely useful at sifting through and making sense of data that would otherwise be out of bounds to decision makers. Examples include sentiment analysis tools that can constantly scan swathes of content on social media platforms to pick out insights, or finance regulatory tools that can ‘read’ complex documents and flag up compliance issues. Over time, a manufacturing plant monitoring tool can ‘learn’ to recognise the various combinations of readings that might indicate performance issues. When these circumstances arise, the issue is automatically flagged up.

In these use cases, AI opens up data streams that might otherwise be difficult to interpret in large quantities. It doesn’t have to make the role of human decision makers redundant. Rather, it picks up on insights that would otherwise be missed and makes sure you are in possession of the full facts before deciding what action to take.

Looking to the future

What about AI’s role when it comes to day-to-day processing decisions?

Take decisions linked to consumer credit, for instance. Where individual employees are left to decide what credit options should be made available to customers, it’s easy for bias to creep in, or for inconsistencies to emerge. If you have an AI-based tool that’s able to process a customer’s details and assess their risk based on set rules, there’s the potential for much more consistent decision making across the business.

But of course, any AI solution is only as effective as the algorithm behind it. To avoid bias (along with risky approvals), continued human oversight is essential. Otherwise, you risk systemising into the decision-making process the very things you want to avoid.

At its best, AI disrupts the human decision-making process. With the ability to read and interpret vast quantities of data, it has the potential to put relevant information at your fingertips faster than ever before.

A recent estimate for the banking sector suggests that we can soon expect decision-making processes to be 34% informed by machine algorithms and 66% by human judgment. This is probably a realistic interpretation of what the future holds: AI will have a big part to play in informing decisions, but the final decision will remain with people.