Companies that effectively use data for their decision-making have a massive advantage.
Yet the reality is that only a few executives seem to master the benefits.
One such executive is Roger Grobler.
He is a South African-born entrepreneur and investor who, over the last 20 years, has consistently generated significant returns by focusing on data-led decision-making.
As part of the Sybrin Game Changers series, I interviewed Roger and asked him to share his views on what steps companies should take to introduce data-led decision-making.
For me, there were ten eureka moments during the call.
1. Data-led decision-making creates multiplicative benefits
Where you can deploy algorithmic decision-making in multiple places in the value chain, you'll get an uplift and then a multiplier effect from which you can get significant increases in the value of that business. - Roger Grobler
The example Roger gave on the call came from his time setting up Real Insurance in Australia.
Real Insurance was able to beat the competition by focusing on small percentage point improvements at each step of their product lifecycle.
For example, a 2% save on onboarding, a 1% save on fraud, a 3% speedup on payouts, a 2% improvement in recruitment and a 3% improvement on referrals will have profound multiplicative benefits.
(I made up these percentages, but you get the idea)
These improvements didn't fundamentally make Real Insurances products better than their competitors. But it did free up budget to allow them to spend way more money buying AdWords, not only making them one of Google's best clients but, of course, also allowing them to amass hundreds of thousands of customers.
2. Don't Compete
Simple advice. Brilliant advice.
At Real Insurance, they didn't directly compete with the broker network. Instead, they went direct, and they went online.
A more recent example is the South African mobile data provider RAIN, of which Roger was one of the founding shareholders.
Although Rain is often compared to MTN, Vodacom and the other major telcos, it doesn't actually offer any traditional mobile phone services. It also doesn't run a network of shops and stores.
RAIN has therefore created a new market segment for customers who only want 4G and 5G services and who are comfortable ordering online.
As email was to fax, data is to voice.
(Check out The Threat Of Rain if you want to learn more about why Rain is a genuine threat to the current incumbents).
3. Know When Not To Hire Data Scientists
I'd never heard this advice before. But it's awesome.
The default for most companies is that hiring data scientists makes massive amounts of sense.
And in a perfect world, that would be true.
But we don't live in a perfect world, mainly because it's full of humans.
And some of those imperfect humans are data scientists who do not ever want to have to work in a boring company, solving boring problems.
Which is fair enough.
If I had spent many years learning cutting-edge skills, I'd want to work in companies that provide cutting-edge opportunities.
But most companies don't have those types of problems, which means that they are highly unlikely to be able to hire decent data scientists at sensible salaries.
And even if they do succeed, it's more likely than not that they will leave before anything useful has been built.
So if your product is boring (from a data-scientists perspective), like, say, a typical manufacturer, but you still want to implement data-led decisioning to, for example, convert all of your untapped sensory/IoT data into something useful, why not look for an excellent consulting firm.
(If you want an intro to an excellent data-scientist consultancy, give me a shout and I'll put you in contact with Chisl Group. I know the founders from my banking days and they are awesome.)
Oh.., and if you are a data scientist that loves solving manufacturing-related problems with algorithms that can reduce error rates, or wastage or input costs...., you are a true unicorn, so please reach out.
4. Good Culture Is The Key
Okay. Time to pivot from strategy to culture.
Well, in Rogers's words...
If you talk about data-driven decision-making and AI and algorithms, the very first thing you need to get right is the company's culture. And that must start with senior leadership and then cascade throughout the organisation. The technology, the data is not going to get your company there if you don't have the right culture inside the business - Roger Grobler
This is why Roger spends a huge amount of his time, perhaps the majority, focusing on culture in all of the companies he invests in.
What does he look for?
How does he create and maintain it?
5. Find & Enable Your Talent Multipliers
If you have read the book by Laszlo Bock, called Work Rules, then skip this point.
For everyone else, particularly the non-techies amongst us, remember this...
A really talented software engineer is worth 100 average engineers - Roger Grobler
Whilst strong leadership teams will have mastered the art of identifying and enabling these rare talent multipliers, the reality is that most leadership teams do indeed struggle.
Rigid, hierarchical organisations will find it the hardest to enable these talented individuals, as they will not fit within the red lines drawn up by the HR policy police.
But if you can break the rules and enable these rare birds by paying out-of-range salaries, offering unrestricted technology access and allowing them to work from Seychelles if they want to..., then you will see exponential benefits in your company.
Simplifying...,as long as these multipliers are not falling foul of your company's credo, just let them do what they want, when they want, how they want.
(If you are wondering what I mean by a company credo, I'll return to that in a minute.)
6. Be Ruthless In Maximising Your Talent Density
If the success of a company can largely be attributed to the quality of its employees, it goes without saying that organisations with poor performers are going to fare poorly.
And yet most companies seem to struggle to remove their worst performers.
Perhaps the idea has gone out of fashion?
Certainly, one famous CEO, I forget which one, said that he'd never fire poor performers as he believes the organisational failure of hiring poor talent should not be passed onto the poor performers themselves.
Noble, but the reality is that if you have a high density of high performers, you'll not only get the benefits of their as-is performance, but you'll also get the additive benefits of them challenging each other, learning from each other, supporting each other and therefore getting even better together.
So go check out what your talent per seat percentages are, and make sure you don't have, and this sounds very machiavellian, but make sure you don't have seats in your company that are wasted by people of average talent - Roger Grobler
(For a great example of this, check out Netflix founder Reed Hastings's book No Rules Rules.)
7. Values are gimmicky. create a credo instead
I was so happy to hear Roger say what I've believed for so long.
Values are gimmicky
Do you remember Enron?
Do you remember Steinhoff?
I remember the Enron values because they were almost the same as one of the banks I worked for.
Respect. Integrity. Excellence. Communication. - Enron's Values.
I've always found the whole idea of values like this completely ridiculous as they are insulting to their employees.
To have to state values like this almost implies that if you don't, your employees will be disrespectful, lazy liers who hoard information for their own advantage.
Credo's, on the other hand, are radically different as they actually create something meaningful about what employees are trying to achieve and how they are empowered to achieve it together.
Take this example manifesto (credo) from one of the world's fastest-growing equity brokers, Easy Equities.
I'd love to work for / partner with an organisation like this, as the manifesto creates an implicit contract as to how we should expect each other to behave.
It also binds these requirements around the goal of the company.
Wouldn't you be inspired to work for an organisation with such a clear purpose?
Our dream is to democratise investing and empower financial dignity for all. We believe that our dream will be delivered through technical excellence, beautiful design, and inspiring storytelling that engages all dreamers and makes investing easy and fun for everyone
And wouldn't it be nice to know that you are working in an organisation where it's safe to fail-to-learn, where you know that the team is more important than the individual and you know that you will be trusted to structure your work in whatever way works best for you?
How many of us are lucky enough to work in an environment like that?
8. Scaling Is Hard. Celebrate Your Operational Teams.
Scaling is hard. 10,000% harder, according to Elon Musk.
And his journey with Tesla certainly gives him the credentials to opine on this topic.
The really remarkable thing that Tesla has done is not to make an electric car, or to be a car start-up, because there have been hundreds of car start-ups in the United States and outside United States. The thing that’s remarkable is that Tesla didn’t go bankrupt in reaching volume production. That’s the amazing part because everyone else did. They thought the prototype or the idea was the hard part, and it is not. It is trivial by comparison with actual production. So it's always worth noting that of all the American car companies, there are only two that have not gone bankrupt, and that is Ford and Tesla. So the seeds of defeat are sown on the day of victory, and we must be careful that we do not do that - Elon Musk
Understanding this is important as it makes Roger's next tip all the more poignant.
Scaled organisations celebrate operational excellence - Roger Grobler
Most companies I've seen are therefore making a mistake, as they continue to focus on their star deal-makers and sales teams. They, like football teams, are rewarding their strikers but forgetting that without the other players, there would be no product or brand from which these stars can shine.
So the message here is simple. Not only, as mentioned in point one, must companies focus on using data-led decision-making to improve every step of their product's value chain.
They must ensure they have rockstars in every area and pay them accordingly.
9. Avoid The Peter Principle
The Peter Principle is an observation that the tendency in most organizational hierarchies, such as that of a corporation, is for every employee to rise in the hierarchy through promotion until they reach a level of respective incompetence - source wiki
You can avoid this by not defining seniority by management status.
So if you've got somebody that's really strong at doing something, their career path should not be defined by how many people they manage - Roger Grobler
As Roger goes on to say, managing people is a skill. Engineering is a skill. Being an excellent engineer does not mean you could be an excellent manager.
By focusing on placing the right people in the right roles, where their benefits are maximised, you will end up in situations where managers consistently have people in their teams who earn far more than they do.
And in case you were not sure, this is a good thing.
So if your organisation correlates salary to managerial hierarchies and the number of boards and committees people attend, you are likely a good peter principle case study.
10. Understand That Change Is Hard
I think the unfortunate challenge with successful old businesses is that they are successful old businesses. They've got these business models that worked for them for forever and a day. You've got managers that sit there. And if you start challenging the goose that laid the golden egg you do so at your peril. - Roger Grobler
To be fair to senior leaders at legacy organisations, in most cases, they realise that data-led decisioning is the path they need to be on, but changing the culture and direction of any organisation with more than a few hundred employees is incredibly hard.
Is it possible?
But I'd suggest only purposeful, courageous and curious leaders should consider taking up the challenge.
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