25 Apr

Why A World-Class Data Culture Is The Cornerstone of Data Success In The Enterprise

Josh Walker

Enterprises are rightly in pursuit of the promise of big data: democratised access to real-time insights into your customers, your products and your business.

But many enterprises are investing huge sums in next-generation technology, which, on paper, should deliver the promised value but, in practice, deliver mediocre results.

One reason they struggle to realise their dream, despite having all the fancy tech, is that the culture isn’t suitable for the ways of working required.

If there isn’t a culture of putting data at the heart of everything that you do (or allowing the right data to get to the right people at the right time), then you can hire the smartest data nerds in the world and you won’t see any return.

In this blog, I’m going to outline five key areas of focus to enable your enterprise to build a world-class data culture that will start to deliver real ROI.

1) You need to rethink your operating model

The data industry is catalysing an organisational revolution that has happened before in other areas of the tech industry.

The Agile Manifesto was penned 21 years ago, promoting cross-functional teams, decentralisation, user-centricity and so on, representing a profound willingness to rethink traditional roles and break down barriers between teams and departments.

This pattern then expanded into new territory a decade later with the arrival of DevOps culture. And now we are seeing the same thing in the data domain.

A modern data culture is decentralised, non-monolithic, cross-functional, user-centric and non-dogmatic.

Rather than being a centralised function or domain, data-centric ways of doing things become infused into all aspects of the enterprise.

If you are looking to reorient your culture around data, you will need to have a similar willingness to break the mould of how things have always been done. Risks will have to be taken and there will be plenty of trial and error involved.

But big impacts need big changes!

If we can learn anything from the past it’s that Rome wasn’t built in a day. And large enterprises, especially, take a lot of time for deep changes to take root.

But looking back we can see that the people who launched successful Agile and DevOps transformations were prepared to deeply rethink how they worked.

Read more about how this approach puts data at the core of innovation for a financial services enterprise here.

2) Culture and business goals must come as a pair

In order to get the business backing required to transform your organisation, you will have to align your data culture obviously and measurably to business goals.

There’s no way you will be able to build a world-class data culture unless you have business backing and it aligns to the business strategy.

Far too many enterprises have expensive data experts that are spending vast amounts of time on projects that are of interest to them but that don’t align with the business.

In order to secure the buy-in, investment and adoption that is required to make your data strategy work, your data teams must have key business objectives at front-of-mind.

Often, there is an expectation on business folk to be data literate. But, as data teams become federated throughout the business and closer to business domains, it’s imperative that they become business literate so that their work is contributing to the business.

3) Supercharge learning with business-wide collaboration

Data is a fluid entity that gains in power by being transformed and shared.

That’s why collaboration is such an important facet of a killer data culture.

Central to this is cross-functional teams and cross-pollination between business domains. Teams learn more when we remove siloes and break down barriers.

Moving away from hyper-specialised teams immediately reduces what we perceive as a skills gap given that teams can be balanced more effectively. The added advantage of cross collaboration and pollination means we intrinsically upskill each other, almost by osmosis.

This is particularly helpful in the data realm. While data engineers are experts at certain niche data tasks, they often lack the software engineering skills to streamline their pipelines, such as continuous delivery or automating their tests. Likewise, software engineers who are building infrastructure aren’t familiar with the needs of the data engineers and their toolsets.

By removing the boundary between the software and data engineers, for example, leads to a cross-pollination of skills that is mutually beneficial for each of the former siloes.

This kind of cross-pollination is a foundational aspect of a data culture that has roots that go down into every corner of the business.

4) Invest in the Growth Of Your People

Data skills are comparatively rare, so you need to take advantage of what opportunities you have to upskill your people.

Fortunately, there are plenty of data skill accelerators available.

The commercially savvy will be able to find the funding to ask someone other than the CEO to approve their upskilling budget for 2022.

The UK is very much on the front foot with a bullish national AI strategy that offers departmental spend and support for building the workforce of tomorrow.

The government website has a list of skills bootcamps and I can connect anyone who’s interested with bootcamps, accelerators and upskilling for both tenured and also early career individuals.

This is a great way of future proofing your workforce, retaining teams and ensuring your company has the skills set up for future success.

5) Become Part of the Data Ecosystem and Community!

Humans thrive on connectivity and community. In the data industry things are no different, with a thriving ecosystem of well-known people, channels, and events.

Enterprises, in particular, might wonder what they can gain from investing their time and effort in the wider community, but it’s critical that your local data culture is plugged into the wider data culture!

An isolated data culture will slowly die, it needs fresh input to keep evolving.

So get plugged into communities through Slack channels, Meetups and industry events that give you exposure to those who are on similar journeys to you.

Here’s a few good ones to name but a few:

- Data Mesh Learning (Slack & now a podcast)

- MLOps (Meetup)

- GTA Data Tech (Slack & meetup)

Final Thoughts

As the famous Peter Drucker quote goes: culture eats strategy for breakfast.

If your enterprise has taken data to the heart of its culture and is buzzing with ideas, skills, connections, collaboration and all the juicy people stuff, then the technology will take care of itself.

Invest in building a world-class data culture and giving your people what they need to thrive and your data transformation will become a turning point for your business.

Having done it in our own organisation and with many of our clients, we are happy to talk and guide anyone through this shift.

If you want to be competitive, you need to sort your data constraints, and that's where Mesh-AI can help. Identify the areas in your organisation that require the most attention and solve your most crucial data bottlenecks. Download our Data Maturity Assessment & Strategy Accelerator eBook.

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