What’s a finance leader to do?
If you believe the hype, automation and AI are flipping finance departments on their heads. But the reality is that many finance teams are struggling to implement the digital practices and data-enabled tools that could turn their departments into an efficient creator of strategic value and insight, not just another cost-centre to be optimised, trimmed, and outsourced.
This is the dilemma last week’s Generation CFO panel (Chris Argent, Mike Rose, Wei Li, Charlie Hudson and Simon Bullmore) debated with finance leaders and industry-experts. Here’s what we took away from the conversation…
Start with skills
Many finance professionals are still at the beginning of the learning curve in terms of the latest technologies that will transform the way we work in the near future. This learning curve needs to start with fundamental digital and data literacy. Leaders need to pay attention to both their skills and the skills of their teams.
It’s about culture, not tech
One reason that skills are so important is their role in creating the conditions for new technology to flourish. There’s a general agreement that the excitement about new technologies needs to be balanced by the reality of implementation. Despite huge investments, data projects have a high failure rate (perhaps as high as 85%).
The problems aren’t with the technology itself, in the vast majority of cases it’s about culture. The ways of working and mindsets that either help or hinder a business trying to do something new. This means leaders need to make a conscious appraisal of the readiness of their department and the wider organisation to take advantage of new technology.
Carefully consider your questions
There’s a beauty in simplicity, but it’s not always easy to cut through complexity and identify a simple question that needs answers. Nonetheless that’s often the best place for finance leaders to start. Time dedicated to identifying then refining questions is a good investment. And one that’s essential to make before investing in technology.
This means considering how the question can be answered, what data might be needed and whether an answer will provide the basis for action that creates value for the business. Getting to simplicity isn’t always easy, which is why many leaders, before engaging technology departments or providers are working with specialist data consultants and start-ups who help them find better questions that have the potential to offer better answers.
Collaboration is key
Addressing cultural issues, implementing new technology and refining questions requires the support of colleagues from across the business. Striking parallels were drawn between the challenges IT and finance face. When seen purely as cost-centres both departments have a tendency to risk and innovation averse decision-making. That’s not to say that the appetite or budgets aren’t there.
But, as evidenced by an example shared by a participant, IT departments in particular often prefer following well trodden paths, with big name consultancies or vendor, rather than trying something new from a start-up, or an internal group. This wasn’t a finger pointing exercise at IT, as there was an agreement that finance departments can exhibit similar tendencies. What needs to happen is a renewed focus on building relationships with other parts of the business that provide critical insights and infrastructure, then working together to get things done.
Sort out the plumbing
Many businesses are still figuring out how to get value from technology investments purchased years ago. A significant part of the problem is getting data from one system to another, and ensuring that the data is fit for purpose – accurate, up to date and in the right formats. The plumbing analogy makes it sound easy. It’s not. Especially when you consider the regulatory environment and technical issues involved.
This is why start-ups have an advantage, particularly in data intensive industries like financial services and insurance. They can start from scratch and don’t have to renovate and reroute the data equivalent of a Victorian sewer system. That makes it seem like a herculean task. But that needn’t be the case. If you can build a clear and strategic view of the data infrastructure you need there’s a flourishing eco-system of technology and consultants who can help join things up.
Make friends with the robots – they’re already here…
Whilst some departments are struggling to keep their existing infrastructure patched up, more agile businesses are already using new technology to make their operations more efficient, and provide better insights to the wider business or market. We need to keep a close eye on both competitors and start-ups in our sectors to see what’s working (hello RPA and apps), what’s overhyped (we’re looking at you Blockchain) and what’s coming next (data ethics, AI & chatbots). It’s not about chucking cash at shiny new boxes, it’s about being able to sort out the hype from the reality and staying competitive.
The key here is adapting and learning. Adapting to new ways of working that automated systems allow, and learning how to work alongside new technology. Yes jobs will change, some may even be replaced, but, as with previous industrial innovations, from mechanisation to the web, new technologies like AI will open up new opportunities.