Water, water everywhere, nor any drop to drink

Comparing data to oil, has become almost a cliché, and although this image correctly translates the potential value of data it doesn’t translate the challenges when it comes to enable that value.

Comparing data to water may be a more accurate way to describe the challenges most organizations face when trying to get actionable insights from their data - Despite being in a sea of data, they can’t benefit from it.

Just like potable water, actionable data is also a scarce resource.

We’ve witnessed, in these last few years, to organizations investing heavily on new IT infrastructure, on new digital channels, leading to volumes of data flowing into their systems increasing exponentially.

And now business leaders want to see value being drawn from all this data – and started investing breaking down the data silos or creating data lakes – to enable them to retrieve those insights and generate business value from their data.

Why is it still difficult to produce this potable/actionable data? Even for organizations that have successful digital transformation processes?

Making data an asset

Gathering all this data is never the objective when engaging a digital transformation process, and most organisations are caught unprepared to deal with it.

They have apprehended the importance of data in their businesses and are looking deeper into data to gain a competitive advantage, implementing machine learning and artificial intelligence to achieve new business objectives and to move ahead of competitors in the industry.

Data needs to be treated like any other corporate asset: A data asset is every piece of data that organizations use to generate revenues, they are currently among its the most valuable assets, and organizations must invest seriously on managing these assets.

Organization must start by identify the business problems that need to be solved, and can be solved using data, and work backwards from there. Data’s purpose is to create business value, so any data initiative must be oriented towards the organization's strategic priorities and key business objectives.

Organizations have invested heavily in technology as a first step toward becoming data-oriented, but these transformations are still hampered by ill-defined processes and business roadblocks.

The success of any data related initiative is measured on how it impacts business performance.

The true measure of success is the quality of the organization’s decision processes; the organizations best able to make the best insight-driven decisions faster will gain the competitive edge.

Rather than undertaking massive change, organizations should concentrate on targeted efforts to build a data-driven culture. Don’t focus on overall data-driven transformation, identify specific projects and business initiatives that move the organization in the right direction.