Creating value from Data


Creating-Value-From-Data

Creating value from Data.

The business world is inundated with data—data about customers, operations, partners, products, services, and much more.

Great as that may be, organizations are struggling to translate that data into meaningful information that has a positive impact on their business. This is primarily due to the fact that management often seeks to tap Big Data without first taking inventory of all of the key Big Data assets available to them, according to a Harvard Business Review article

“We contend that in the absence of a clear understanding of the knowledge drivers of an organization’s success, the real value of Big Data will never materialize,” the article notes.

The first step to leverage Big Data and derive true value from it is to identify and map the knowledge assets that are critical to future growth.

“Your list of key assets should ultimately include some that are ‘hard,’ such as technical proficiency, and some that are ‘soft,’ such as a culture that supports intelligent risk-taking,” the article notes. “You may also have identified knowledge that you should possess, but don’t or that you suspect needs shoring up. This, too, should be captured.”

Next, assets can be populated on a grid with two dimensions: unstructured versus structured and proprietary versus widespread. Once populated, this knowledge map can be used to uncover valuable insights.

For example, the article notes that sourcing managers at Boeing mapped the critical knowledge assets in their global sourcing activities.

“They saw that cost-related knowledge—performance metrics, IP strategy, and supply-base management—was well structured and widely diffused,” the authors point out. “However, knowledge about supplier capabilities, although codified, had not spread throughout the Boeing sourcing community. And other knowledge that was important to future value creation… was neither codified nor widely shared.”

In the example cited, Boeing determined that it was placing greater emphasis on technical efficiencies than strategic growth, which prompted the company to launch new initiatives, including a program to help employees with a deeper understanding of geo-political influence to put structure around their knowledge and share it with others in the company.

The article points out additional steps companies can take to further refine the knowledge map, including:

Think carefully about which proprietary assets can be structured so that they can be leveraged for future growth

Create value by sharing knowledge externally by selling or licensing intellectual property

Purposefully decide what information should be diffused within the company

“So, your future success depends on developing a new kind of expertise: the ability to leverage your proprietary knowledge strategically and to make useful connections between seemingly unrelated knowledge assets or tap fallow, undeveloped knowledge,” the article concludes. “The most challenging -and highest-potential  – opportunities often come from spotting connections between disparate areas of expertise (sometimes inside the company, sometimes outside it). The analytic techniques that can turn Big Data into big knowledge are used partly in hopes of finding such unexpected connections.”