Data-Driven is a Team Sport

The biggest obstacles to creating data-driven businesses aren’t technical; they’re cultural.

Being data-driven is not about data, it’s about business. So, it makes all sense that is should be business leading the process.

One of the biggest obstacles for successful digital transformation processes is the lack of involvement from the business.

The preconception that data initiatives should be in the hand of data people is still prevalent in most organizations, everyone else tends to be seen as part of the problem never the solution, either because they’re not up to date, unprepared to handle data or even resisting to any changes.

Experience tells us exactly the opposite.

Most people are fully aware of the importance of data, and more importantly how data impacts their daily activities and processes, and how it impacts business.

The shift of mindset must first start on the management teams that need to start seeing people on the business side as a critical element in their data strategy.

Asking people on the business side where they the opportunities to use data to improve their processes and work has usually a beneficial effect by identifying critical pain points where data can make the difference. Starting with business areas than can clearly identify and measure the business impact of bad data on their processes - In every organization the opportunities to identify these cases are abundant. Across all the business areas there are pain points related with the quality of data and identifying them is not a challenge.

New sales reports are unreliable? Loan yield vs. risk rating indicators are inaccurate? AML processes are returning too much false positives? Customer segmentation is imprecise? Customer satisfaction scores are sketchy? All of these are probably data related issues, although sometimes they can be process related, but who better to identify them that people that have to handle these issues on a daily basis.

As data teams thrive to gain their space and visibility within organizations, some of the resistance ends up coming from their side, generating a tendency to exclude everyone outside the “data space” from their initiatives. Shifting this approach to building the business cases with those willing to defend it. – Those who feel those impacts directly. Once a critical pain point is identified, you’ll have a business stakeholder that can passionately and effectively articulate the impacts of poor data quality in their processes and that will be eager to defend the project.

It is simple enough to describe how to inject data into a decision-making process. It is far harder to make this normal, even automatic, for employees — a shift in mindset that presents the true challenge.

Developing a robust data-driven business strategy, and simultaneously a business-driven data strategy that involves everyone in the organization - business leaders must adopt a strategic approach and fully commit to realizing the value of their data assets and to generate business value.

Project graveyards are cluttered with failed data initiatives that did not deliver clear ROI. With a strong leadership and business focus, data initiatives will pay for themselves by adding real ROI to business initiatives.

In a data-driven economy, CEOs and executive leadership must promote the organizations’ data strategy into the business and out of the technology context, as any other corporate asset data’s purpose is to create business value, so any data strategy must be oriented towards the organization's strategic priorities and key business objectives.

Those business objectives must drive the development of the data strategy, focusing on use cases that support business objectives, creating traction and increasing the awareness across the organization and will end-up acting as the motor from within the organization for a successful transformation.

Data must be understood as a fundamental part of business, not a set of technological projects. The development of the data strategy cannot depend on the limited resources and throughput of the data teams.

Business users must be enabled to a data driven approach where they can improve and control the quality of data and address and mitigate problems.

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