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4 tips to create a data driven company culture

Despite significant investments into data initiatives, many large organisations are not getting everything they want from the data in their organisation, and still have some way to go to meet their data objectives. 

This year’s New Vantage Big Data and AI Executive Survey of 85 Fortune 100 executives found that just under a quarter (24%) of respondents say they have ‘created a data-driven organisation’.

Despite 99% of respondents having made a significant investment in data initiatives such as Big Data and AI, only a third (30%) of respondents agree that they ‘have a well-articulated data strategy’. 

The biggest struggle many firms face is not related to technology limitations but cultural barriers, with 92.2% of respondents identifying people, business processes, and culture as the biggest challenge to becoming data-driven.

This is having a distinct effect on data outcomes, with just a third of respondents (29.2%) agreeing that they are ‘experiencing transformation business outcomes’. 

These challenges are not confined to Fortune 100 companies. At Think Evolve Solve, many of the organisations we work with are experiencing the same cultural challenges in establishing their data strategy. To help build a data-driven culture across the workplace, we recommend the following activities:

  1. Manage data as an asset, not a by-product

Data is critical to many core business processes we complete today but is often considered as a by-product of technology and processes, rather than an asset in its own right. This can result in data being collected, processed, and utilised incorrectly by business teams.

To mitigate this, we recommend involving your business teams in creating an Executive Data Framework. This is a list of all the business assets that are required to run the organisation, with a description of its use case and categorisation of why it is required. This view of the data assets should not be confused or constrained by what is available but should be looked at from the perspective of the business model – why data is currently utilized, what format it is required in, and how new data could potentially support this process. 

Linking data assets to the business model can be transformative for business teams and often enables the identification of significant right-sized data initiatives that can be successfully delivered by the business. By making this framework available to consult in the future, companies can drive organisational alignment and build better data literacy in non-technical teams.

  1. Curate output data

The volume of data created by an organisation is rapidly increasing, to the point where companies may lack the bandwidth to process and utilise it effectively. Taking a curated approach to data delivery is critical to the successful implementation of a data-driven organisation and showcasing the effectiveness of data to business teams. This approach minimizes the amount of manual data preparation required of business teams, reducing the chances of incorrect use and ‘data fatigue’ amongst fewer data literate employees. 

By identifying the use case for data in the Executive Data Framework, it’s easier to deliver this data in a business-ready reporting view. Despite a proliferation of business-friendly tools to process data visually, many organisations still miss opportunities to present data in a way that aligns with the business model or process, which can limit data adoption.

  1. Centralise responsibility for data 

Despite being heavily dependent on data to inform business processes, many business teams that consume data day to day have a lack of visibility into data processing workflows. As a result, they have a limited ability to problem solve interruptions in the data workflow that impact their role. 

Troubleshooting or adding new data feeds can result in communication challenges between the business and technical or data teams, where distributed responsibilities for data sourcing, preparation, and usage result in a disconnect between business needs and technology. This can result in a long time to resolve issues and a lack of accountability and buy-in for data initiatives. 

To resolve these challenges, many organisations have been working on centralising data sourcing and data preparation activities, allowing business teams to get better visibility into issues in the data supply chain and communicate effectively with the right stakeholders to resolve the problem. By transferring this ownership and management of core data assets to the business, organisations can establish a much more integrated data culture. 

  1. Align core data KPIs to business objectives

Another vital element of the data strategy is setting up core KPIs to measure success. By connecting your data strategy to business objectives, business teams will get a clearer picture of how data supports them to achieve their organizational goals. 

Start by highlighting the business KPIs and develop your data strategy around these long-term goals, and identify the data assets that contribute to them. By designing the data strategy around existing business objectives and communicating the relationship between data assets and the business objective to key stakeholders, companies can build awareness of the value and impact of data on an organisation. 

Create a data-driven culture

At Think Evolve Solve, we’ve made it our mission to create a simple, fast, and effective way to build data strategies that work. We support companies across multiple industries to create a data-led digital strategy that establishes data as a core business asset and enables it to power your organization effectively. 

We help minimise the complexity of data with our Executive Data Framework, and enable business teams to take an active role in data management with our data supply management tool, gather360

Find out more about our Discovery Program

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