There is a classic trade-off between rules and innovation, particularly if you work in a heavily regulated industry. So how do leaders balance the need for stability, compliance and certainty with a 21st century appetite for adaptability, agility and disruption? One approach is to learn to think a little less like a ruler, and more like a machine.
Late last year I gave a talk in Manila for the corporate governance team of a major telco. The company was heavily scrutinized by regulators and maintained a traditional governance regime. Not surprisingly, that meant it wasn't easy to try new things. Many in the company wanted to be rule-breakers, and yet, most of time, they just ended up getting broken by the rules.
Rules are fickle things. They can appear as authoritative as a set of commandments on a stone tablet, or as notional as a speed limit on a back road in the country. In either case, however, rules are not the natural enemy of innovation.
The reason for that is simple. Most rules are actually designed as short-cuts. Rules are heuristics, designed to speed up transactions when all parties can't assume that they can trust each other. As such, a good rule should not be immovable, but in fact, the very opposite: a principle subject to constant evaluation against a goal of efficient governance.
Reimagining the role of rules is relevant when you start to think about how a company might work in the 21st century. For example when Tony Hsieh, the CEO of Zappos decided to get rid of job titles - it was more than just a fancy experiment in company culture. He wanted to see if Holocracy would work as a more effective set of rules than traditional 20th century management.
Whether it be smart contracts, distributed ledgers or algorithmic decision-making, the company rules in the future may start to look more like lines of code, than clauses in an employee handbook.
For anyone working in a highly regulated industry or company today, there are a few things that you can start to think about:
1. Patterns not punnishments
Set some simple, clear values to guide behavior and then consider a machine learning approach to compliance. Look for patterns that suggest misconduct, rather than attempting to codify and limit specific actions.
2. Designing not doing
Shift more decision making to algorithms, and devote more of your time to designing them. Rather than setting rules and enforcing them, shift your focus to defining problems, reframing results and debating predictions.
3. Sharing not shaming
Work with ecosystem partners and regulators for sharing transactional data from your platform in real time. In some jurisdictions, this approach is already eliminating the need for traditional corporate tax returns.
The last few years have yielded significant breakthroughs in AI, largely because of the shift from trying to use advanced programming to model entire worlds with thousands of rules, to approaches that let machines learn for themselves. In my view, the key to reconciling the trade-off between rules and innovation, is to take a similarly adaptive approach to the way we design companies.
Rules may not be made to be broken, but they should certainly be open to being constantly re-written.