The automation of finance operations in multinational companies: key takeaways

Following some interesting discussions on my thesis from the Executive MBA course at the Prague University of Economics and Business, I thought I might lay out some key takeaways for anyone interested.

The thesis was based on a series of qualitative interviews with finance professionals, broadly split into executive (VP to CFO) and mid-management (Managers and Directors) levels. The broad aim of these interviews was to find out what activities are being automated, and how.

Key Insights:

1. There is a general difference in mindset between those at executive levels, and those at managerial levels, hence my guidance here follows that split.
2. There are common fears and expectations that automation technologies will replace jobs, notably based on AI, but the picture is not as simple as all that, and the process will take longer to bear out than most people expect.

Here are the high-level findings:

Guidance for Executives

Focus: Executives should focus on the overall business case and on end-to-end processes rather than individual tasks.

Tools: The tools under consideration are generally the overarching ERP, CRM and Business Intelligence platforms.

Risks: The key risks inherent in deploying such platforms include a high failure rate, meaning not achieving the business case, or even an outright failure of the implementation.

Mitigations:

• Executives should ensure a dose of realism in any business case,
• In particular, they should ensure plans include significant change management activities, including close post-implementation support.
• Having a centralised team looking after implementation rather than leaving it to local teams ensures central control and also builds critical experience and knowledge.
• Using a modular rollout instead of trying to do everything at once helps lower the risk for any given part of the deployment, building knowledge and momentum.
• Having a strong team is highly important: executives should hire right, foster flexibility and develop the skills and mindset in their teams needed to deliver great service in changing circumstances.

Guidance for Management

Focus: Mid-Management interviewees were more focused on the outcomes under their remit and on automating the tasks that help achieve those.

Tools: The tools used vary, but by far the greatest use was of functionalities in the same ERP, CRM and BI platforms mentioned above, supplemented with tools like SQL code, Excel, RPA and Process Mining applications.

Risks: The key risks for mid-management mostly concerned change management;

Mitigations:

• Managers and Directors should make change management a priority, ensuring repeated trainings and materials are available, with support from the project team during implementation, but also ongoing support in the months after it.
• A focus on team quality generally remains key, with flexibility and a focus on learning, delivering value and being willing to work well within the wider organisation being particularly valued.
• The right tools should be used for the tasks at hand. In particular, the tools should be chosen according to the needs of the business, rather than procuring the tools first and then trying to fit those to the needs of the business.

Will AI Replace Workers?

Well, yes, but that's not the whole story. The reality is that automation technologies have two effects on businesses: they reduce the demand for workers doing routine work, but they also increase the value and compensation of the workers remaining in production. Furthermore, the remaining work is made more interesting and engaging without the routine tasks. The result is a polarisation of jobs, with skilled jobs becoming more valuable and enjoyable, but unskilled jobs seeing higher competition and stagnating or falling pay.

Moreover, the introduction of new technologies takes significantly longer to play out in the workplace than people expect, largely because processes need to be redesigned to take advantage of those technologies. Futurist Roy Amara put it best when he said that the impact of new technologies is overstated in the short term and understated in the long term. From another perspective, the new AI-based technologies are really just a continuation and new aspect of the computing revolution which has been ongoing since the late-1970s, from mainframes through to desktop computers, the internet and the cloud. Each replaced jobs and streamlined operations, but the process is best measured in decades rather than years.

So for business leaders, teams concerned about job security can be reassured that they will deliver more value with less routine work, improving their own job prospects in the process. Additionally, these changes unfold more slowly than many anticipate, giving plenty of time for adaptation. There do, however, remain important public policy implications needing careful consideration.

Want to learn more?

Feel free to ask me for a copy of the thesis. I will be happy to oblige and to answer any questions you may have.