What does it take to be genuinely data-driven?

Dora Mitter, Junior Data & Insights Consultant at Agilisys, explains how to bring together technology, people and processes to create a highly efficient data-driven organization.
Dora Mitter, Junior Data & Insights Consultant at Agilisys, explains how to bring together technology, people and processes to create a highly efficient data-driven organization.

Some of the most valuable assets to any organization are its data and insights. They can reshape how decisions are made and revolutionize how knowledge is managed, ultimately transforming outcomes and changing lives. But what steps are required to become genuinely data-driven?

Breaking down barriers and increasing cooperation are some of the benefits of data. Data can support in making well-informed decisions by creating more opportunities and the deriving of deeper insights. In turn, this builds fairness and consistency, leading to greater trust in data and the organization. That’s on top of improving the customer experience with better access to data, more accurate interventions and reduced duplication of assessments and engagement.

Data brings endless possibilities, especially when organizations become genuinely data-driven to the point where unlocking the value of data becomes second nature. While this is not easy, it is possible. For me, there are five principles for data and insights that help organizations make better use of data.

1. The outcomes

Investing in better data is essential. But unless it is improving outcomes through better decisions or more personalized support, that investment is likely to be wasted.

I have seen organizations trying to gather any data they can, cleanse it and hope patterns will emerge. When they do, what happens next? The ensuing outcomes often disappoint with no plan of what to do with this information, what the end goal is or how to use it to make a difference.

It’s far better to take an outcome-focused approach. In this way, the organization can exploit data properly and open the door to myriad activities with tangible outcomes. To do so, the business needs to clarify what questions it wants answering and have a hypothesis for intervention. To that end, the organization must make sure it prepares the relevant data, cleanses it, overlays datasets, analyses it and then looks for patterns that will allow it to answer any questions, target resources, and improve outcomes.

The key is to align investment in data and insight to organization priorities, know what questions you want answering, be purposeful, and not fall into the trap of doing data for data’s sake.

2. Taking a seat at the top table

To harness its full potential and for an organization to become intelligence-led, data needs to be treated as a strategic organizational asset – like human resources (HR) value people or finance value money.

Equivalent assets have entire departments looking after them and a long-established presence at the top table (for example the HR Director, CFO or CTO). It still, however, remains rare for a strategic leader to be responsible for the organization’s data. Finances have board-level implications, so we expect a board-level CFO – data can have an equally powerful role, yet CIOs and CDOs) often remain in middle-management. Compelling leadership and a mandate for change are essential in changing how people work with and value data.

3. Quick wins versus long-term gains

So, should you be focusing on quick wins or long-term outcomes for your data-led initiatives? The answer is both.

Why? Think about learning a new language. We start with essential words and phrases, and the early progress can be exciting. At this point, you generally begin to understand how the language works and choose what to develop next. However, you know that you’ll only ever be fluent when you’ve mastered the foundations. To succeed, you need to balance the excitement of quick wins with building the foundations that enable you to advance.

Data programmes are much the same. Quickly driving measurable value, for example, through insight use cases, is a prerequisite. It binds stakeholders, creates a buzz and secures investment. In parallel though, it is important to understand the value in what might be considered a less glamorous side of the work, such as data cleansing, which is needed to build sustained success. Whilst striking the right balance can be challenging, it will bring the whole organization on the journey if done right.

4. Just technology?

It is important to remember that technology alone can’t solve all our data problems. Simply investing in technology and expecting it will be enough to set the organization on the path to becoming data-driven, is not enough. I don’t want to downplay the importance of technology. After all, it’s a critical enabler that allows the analysis, storage, visualization, and sharing of data. However, successful data transformation requires a roadmap that defines technology and the people, their culture, skillsets, ways of working, and the processes that enable the improved use of data and insights.

These are much like a jigsaw puzzle – no two pieces are the same, but all are needed to complete the picture. Only by bringing technology, people and processes together will a modern, highly efficient genuinely data-driven organization be created.

5. Data and the decision-making process

To make the right decisions at the right time, organizations must have objectivity and confidence. For that, they need knowledge based on tangible, solid evidence.

The insights gained from data enable organizations to better understand their situation and draw conclusions that can be turned into actions by making informed, evidence-based decisions. Without it, decisions are based on assumptions and gut feel, which could likely result in a failure to predict the impact and outcomes.

We need to evaluate and appraise the data continuously, the outcomes they drive, and refine the insights and actions that result. By doing so will lead to invaluable information that organizations can’t afford to miss.

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Following these five principles will go a long way to successfully transforming your organization into one that’s genuinely data-driven so that you can improve the customer experience, gain greater internal credibility and set your organization along the path to success.

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data, Big Data, What does it take to be genuinely data-driven?

Amber Donovan-Stevens

Amber is a Content Editor at Top Business Tech

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