The essence of being a data-driven organisation is that everyone in the organisation who has to take a consequential decision expects to have the relevant data at their fingertips. The two critical factors here are that data must be (a) accessible and (b) useable, for staff apply up and down the company, from the C-suite to the frontline. This is the case whether the data is used for a complex machine learning model or simple visualisation. In a data-driven organisation, everyone expects to have data available to help them reach the best possible decision.
Top three benefits of having a data driven culture
Efficiency. This is the most obvious benefit. If you can reduce marketing spend by targeting those customers who are most likely to turn into high value customers, there’s a clear efficiency in terms of future growth by reducing your cost of sales.
Service Quality. This ties tightly into efficiency. If you can deliver superior customer service through interpreting analytics, you have an immediate competitive advantage over your competitors.
Speed. The third benefit that really matters is the ability to make good decisions faster. If there is one lesson that 2020 has taught us, it’s that speed of decision making is critical. It’s important because a lot of companies are realising that they’re having to compete against the likes of Amazon in the online retail space — and often, especially in the retail world, being first through the door is the key to success. Having all your data in the right place at the right time can help you take the right decision, which can have a make-or-break outcome.
Making the switch
Becoming data driven is a significant change for most companies. Companies that are designed to be digitally native from the start have an in-built advantage, as their technologies can develop organically and scale with the company, with the staff adapting as technology changes. In digital native companies, rather than technology being a barrier to change, it is a central part of the company, a source of advantage, and a reflection of the prevailing culture. By contrast, in many companies, technology is brought in as a result of procurement process that may be better or worse, and where incumbent suppliers have a large advantage. Often one-size fits all solutions are imposed from above, with limited input from users.
Having said that, technology infrastructure issues can always be overcome if there’s the will to do so. The difficulty is generating that will in the first place, particularly among senior leadership, and helping them to recognise that this scale of transformation involves changing a business’ understanding of what it does.
If this is done effectively, the business will come to see itself as a technology company. Just as Google is a technology company that happens to sell advertising, and Amazon is a technology company that happens to be in retail. That’s how those companies think of themselves, and that’s how a lot of companies should think of themselves if they want to level the playing field.
How to think like a technology company
There are a few steps involved in changing your company’s mindset. There are the obvious technical steps, such as understanding your data. Most companies realise that, without that understanding, they can’t get started.
This is about asking what data you have, what data you can acquire, and what data you are under-utilising. Many companies have a lot of data on customer feedback, for example, which is free text data generated by customers. It’s stored somewhere, not much is done with it and it’s not really used. That company is missing the insight from a huge trove of information that they already hold.
Connecting the data to the problem
Every company should seek to understand how they can use their data to solve their high value business problems. This is the first step in understanding how to become data driven. This leads on to a whole series of questions, such as ‘do we have a technology architecture that allows you to deploy an analytics model?’ It’s no good having a proof of concept that’s not deployable. If your data science team can’t deploy models into production then the team is just a cost centre that doesn’t add any value. So it is worth putting considerable thought into how to build a technology architecture that allows us to exploit our data assets.
Focus on the skill sets you have
Another critical question is ‘does the company have the necessary resources and skillsets internally to do be a technology driven organisation?’ Having the right talent in your organisation is key. If you take a look at the skill sets of your employees and compare them to the skill sets that you’ll need in a technology-driven organisation, you’ll probably find that there are opportunities. For example, your technology team might have a Sys Admin, and you might need a DevOps engineer. Those two skill sets are fairly similar. Implementing a programme of upskilling and personal development allows that Sys Admin to gain the skill set they need to be a fully qualified dev ops engineer and deploy enterprise level technology across your business.
Get buy in from the top
Culturally, the senior leadership buy in is often the key factor. Their willingness to push a data-driven culture throughout the organisation will really engage everyone and ensure that everyone is working towards the same goal, and sees it as a critical part of their own development and reward.
Creating a culture of enablement is central to success, because implementing a digital transformation strategy can be hard work at first. It’s important that senior leadership engages in making it clear that technology is there to allow every employee to do their job better. It can automate the repetitive tasks to let people concentrate on the high value tasks; the complex, people-centric tasks that humans do better than machines.
The most successful digital transformations we’ve seen are ones where the C-level is highly engaged in bringing the whole company along with them. Becoming a data driven organisation is not something that the technology team can ‘do’ to the rest of the business. The drive to achieve it needs to run throughout the whole business, starting from the top.
What’s next?
In 20 years being data-driven will be the norm. We can already see that in Silicon Valley — many start-ups now integrate AI into their product from day one. In large enterprises, it will take a little longer because it’s harder to turn the ship. The reality is that every business will get there because economics will force it. If you use your data effectively, you’re making better use of resources, your profit margins are higher, you retain the best talent — and you’re in tune with your customers.
