How to kick-start your path to a truly data-driven culture

Whilst the business benefits of data and analytics have been widely explored, the importance of a data-driven organisational culture has not been as widely championed as it should.

Indeed, data-driven culture came out on top in a list of activities crucial to data and analytics team success in a Gartner study published in October 2020.1

A data-driven culture is the collective set of behaviours, beliefs, values and actions expressed and taken in day to day activities. It’s vital to business decision-making because two main factors that inform the decisions we make are the process and mindset (i.e. our beliefs and values) we have in mind when making them.

Culture also involves knowledge sharing, learning and development between peers and the means and level of practice and process adoption throughout an organisation. In this article, we’ll look to provide you with some culture kick-starters you can take to accelerate your journey towards establishing a truly data-driven culture.

These pointers do not constitute a ‘big bang’, all-at-once approach. Instead, they should provide a series of immediate, small but actionable changes to support the foundational aspects of a data-driven transformation. Keep in mind that these changes should be relatively simple to roll out, aiming for low resistance activities that encourage adoption and support longer-term roadmap milestones.

By making manageable increments in your data and analytics journey you are actively managing change within your team or organisation, which is key for success. You should aim to go at a pace that is manageable for your team, based on existing skillsets and current levels of data literacy.

With that in mind, here are 5 ways to kick-start you on the road to data-driven decision-making:

1. Managing change

People are instinctively cautious about change, and often outright resistant to it where it might be perceived to have a negative impact for them, or where they may (often mistakenly) think it will result in increased workload for them. This is especially true with data and analytics, with many people assuming they’ll lose power or fall behind the rate of change.

As such, make sure to communicate how you’ll support employees through these changes, and emphasise the personal development opportunities that come with business model transformation. Hold regular one-to-one or group meetings to eliminate any negative feeling, and upskill individuals and teams so they can fully participate in the new data-driven culture.

2. Community communication

Make data a key focus in your community-wide communications. It should be part of the conversation, and the aim is to increase overall knowledge and education around data and analytics.

An example of how you can do this is to introduce a data-focused section in newsletters, team-wide emails or bulletins. Including defined business KPIs reinforces why analytics is important and how it results in improved outcomes and success. This will also help employees that feel uncomfortable asking questions in public, and increase the overall data literacy of your organisation, bit by bit.

3. Internal case studies

Don’t be afraid to shout about your analytics triumphs. Bang the drum about exemplary internal analytics case studies and the results they’ve delivered for various business domains. Often, organisations fail to encourage the uptake of data-driven decision-making because there’s no obvious tie-back to the benefits of doing so. Again, always aim to quantify these successes.

Make sure management call out results driven by data-driven methods where relevant, and do this in your own meetings with team leaders to achieve buy-in from them.

4. Real life examples

The start of a data-driven transformation is often characterised by a lack of awareness within organisations of the opportunities that analytics can unlock. This can hamper adoption and decrease the chances of your data and analytics strategy being a success.

To avoid this, use real life examples that make it easy for your employees to see the benefits they could enjoy from a data-driven approach to work. Empower team leaders to introduce news stories and reputable research as topics of discussion, and always aim to quantify success. Again, this will bolster trust in your data and analytics strategy and keep the upside firmly in mind, which will in turn drive adoption.

5. The “Ronseal approach” – it does what it says on the tin

Projects are often given non-meaningful names, confused by excessive creativity or fixated on acronyms. To avoid this, follow the simple approach where your projects do what they suggest they’re going to based on names and terminology used. Put conventions in place for outcome-based naming conventions that point to who the project is aimed at (e.g. who is the stakeholder?) and what the overall aim is (e.g. customer retention). You should use the same approach when defining and naming any element of your work, such as KPIs and reports.

This will keep your teams on track throughout different phases of the project, and keep business goals in full view as they look to action analytics insights.

To support this, you need to have effective definitions in place: define, define, define. This links back to effective communication. Removing ambiguity is key to driving adoption, and especially important in a field such as data and analytics, where there are lots of technical terms and reams of information to make sense of.

Get rid of this ambiguity by defining wherever you can. Consider creating glossaries of commonly used terms, or putting together presentations and written materials which can be used in meetings, one-to-ones and stakeholder groups. Everyone should be reading from the same page to ensure consistent and effective adoption, enterprise-wide.

The behaviour changes required to drive a data-driven culture transformation require thoughtful communication and a systematic plan that prizes influence and support over command and control. While a top-down approach that presents overall business objectives is vitally important, you must also consider how team leaders and managers can make changes ‘locally’ in their teams.

This article is in partnership with TrueCue as part of our Data-Driven SMB series. For more information, advice and resources on how to accelerate your organisation’s data and analytics maturity, click here.

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