Making business impact with data: what does it mean to become data-driven?

Challenges in Building a Data-Driven Organisation

Becoming data-driven is a goal that many companies strive for, but it’s not without its challenges. One of the main hurdles is building a compelling data strategy that resonates with business leaders. The frustration arises from the delays in delivering data and analytics, which are crucial for achieving meaningful, relevant, and timely business outcomes. Additionally, there is often a lack of financial commitment and organisational attention dedicated to data and analytics initiatives. Despite investing significant time and resources into creating a data platform, many organisations find themselves dissatisfied with the outcome.

The Journey of Data Strategy

One common misconception is treating a data strategy as a one-off deliverable instead of a continuous journey. Just like a business strategy, a data strategy should adapt to the ever-changing business environment. Currently, we are facing disruptive changes and challenges, including decreasing product margins, supply chain disruptions, rising energy and labor costs, fluctuating financial markets, and inflationary pressures impacting consumer confidence. Your data strategy should be flexible and relevant, keeping pace with the dynamic business landscape. 

The True Value of Data

It’s crucial to understand that data holds zero value on its own. In fact, it can be a significant cost. To derive value from data, you need to have a clear and agile business strategy that incorporates data. At Google and Devoteam G Cloud, we work with OKRs (Objectives and Key Results), which allow us to align data use cases with business objectives. While OKRs may not be the perfect fit for every organisation, we’ve observed that aligning data use cases with the business strategy leads to increased satisfaction for both parties.

Use Case Prioritisation Matrix

To create a data-driven organisation, it’s essential to prioritise and categorise use cases within broader business initiatives. By turning your data signals into actions, you can gain competitive advantages and drive tangible business impacts. These impacts include improving customer experience and increasing revenue generation, enhancing operational efficiency, and enabling better management reporting and decision-making. Categorising your use cases helps you focus on specific areas where data can create the most value for your business.

This is what your use cases can look like: 

Customer experience and increase revenue generation

• Improved customer experience
• Improved customer support
• Increased sales
• Increased customer retention

Operational efficiency

• Stock optimisation
• Order prediction
• Improved product quality
• Accelerated product development and delivery to market
• Cost reduction
• Increased productivity with talent acquisition, retention and development

Management reporting

• Better decision-making by using the next 
• generation of intelligent tools
• Self-service BI
• …..

Accelerating Value Creation Over Time

To exponentially accelerate the value creation over time, you need to focus on three key areas: data experiences, data economy, and data ecosystem. Data experiences involve creating productive user experiences that enable all users to access and create value from relevant data. Establishing a data university, pivoting from role-oriented to product-oriented teams, and defining data principles aligning with priorities are crucial steps. In the data economy, you should ensure that data can be published, discovered, built on, and relied upon. Encouraging teams to share data as a data product and implementing data governance practices are vital. Finally, a unified, open, and intelligent data ecosystem with end-to-end capabilities supports your organisation’s data-driven journey.

Want to learn all the details about adding value with data? Read this Google Whitepaper that covers the 3 components in detail. 

Adopting a Use Case Driven Roadmap

When implementing a data strategy, it’s important to adopt a use case-driven roadmap. This approach ensures that each use case is given the necessary attention and resources. The roadmap follows a logical sequence, starting with creating the data strategy and assessing and planning. It then moves on to building the necessary data foundations, including data ingestion and cataloguing, data modelling and transformation, and activation. This roadmap can be applied to various use cases, such as corporate insights, performance and customer experience, and operational excellence. Each use case follows a similar progression to extract maximum business value from data.