In the beginning, there was chaos. A large part of work is organising chaos into order; first into systems, and then into processes.

The emergence of blockchain, robotics process automation, IoT, artificial intelligence, mobile apps, ERP extensions, has propelled businesses and their carefully-loved legacy systems into obsolescence. With the world moving into digital-driven efficiency, old legacy systems that worked fine for the 20th century are still haunting us well into the 21st. The problem, really, is that people don’t like change.

Things are that way because they got that way

Today, Google Now and data analytics have conditioned us to expect real-time personalisation at every point of every customer journey. When your phone tells you to put on a coat because it’s colder outside than it was yesterday, and to get to leave earlier because of traffic, personalisation has achieved real-time intelligence. It’s about understanding the customer’s context.

But outdated systems prevent older companies from achieving this; they lead to fragmented customer journeys, broken processes across multiple systems, and a general lack of efficiency and stunting of growth.

Legacy systems tend to work – but only just. There is enough efficiency in them that businesses keep finding excuses not to update their infrastructure and their model. “Things are that way because they got that way,” claimed the 20th-century economist, Kenneth Boulding. [1]

His point: structures exist because, at some point, they worked. The process of evolution designs processes, and further evolution is often preferable to revolution. Before taking down a pillar, you must understand what it holds up.

But sometimes, revolution is needed. The more common problem by far is that people prefer to hold on to process for its own sake; a sense of safety, or to protect personal fiefdoms built around them. “It’s always been like this” and “there isn’t enough budget” suffocate change; often they are excuses rather than reasons, which vocalise an opposition which comes from the gut.

Resistance to updating a legacy system is therefore to do with mindset.

Not having the budget demands shaking up priorities; hindrance caused by silos is about valuing communication; not having senior support is about business models. Addressing over-complex and tangled systems requires orchestration across people, technology and devices. It requires a huge amount of time, effort and money.

The solution

The solution to old processes must encourage a mindset shift. The Harvard Business Review considered the top contributors to resisting change as the loss of control resulting in uncertainty, fear of more work, concerns about competence. [2]

The automation of many processes saves businesses time and money; and the greater a proportion of a given process is automated, he more opportunities there are for data collection and data-led improvements.

Adidas’ reimagining of their supply chain reduced supplier onboarding time by 50%, while Old Mutual saw onboarding customer time cut by ten times. BPM company Triaster calculated that one of their clients could save over £300,000 per year by improving just one process. While a legacy system might still just about work, implementing process automation saves huge amounts of time and money. It’s worth the effort.

Scrapping a legacy system completely is not necessarily the answer: rather, connecting into existing APIs and surfacing all the good data that’s been trapped in it could be the right thing to do.

Data is a skeleton key in making business arguments which can produce better outcomes. Data scientists can claim to make objective arguments about how to improve process – and automation enabled data collection which is objective and measured. “Human” problems – training, creative decision-making, and sticking to old processes, make way for a continuous optimisation based on data.

Process automation is no longer a funky thing to iterate on top of your business model. Very soon, it will need to be central to your infrastructure if your business is going to keep up with the pack.

1. Heusser, M. et al. (2011) How to Reduce the Cost of Software Testing. p97.  [online] Available at: https://books.google.co.uk/books?id=elEHzWQ4rTYC&pg [Accessed 12.12.2018]

2. Kanter, R. M. (2012). Ten Reasons People Resist Change. [online] Harvard Business Review. Available at https://hbr.org/2012/09/ten-reasons-people-resist-chang [Accessed 12.12.2018]

3. Mulholland, B. (2017). 17 BPM Statistics to Help You Increase Efficiency in Your Business. [online] Process St. Available at https://www.process.st/bpm-statistics-increase-efficiency/ [Accessed 12.12.2018]

This breakfast was conducted in partnership with Bizagi. Bizagi is an enterprise software company whose competencies include Business Process Management.