Strategies for Unlocking the Value of Third-Party Data

For almost every data-driven organization, third-party data has become a critical asset. It provides much needed context to support the use of internal data and derive value.

While organizations inevitably amass a data footprint that provides some insight over their direct sphere of influence, third-party data is required to provide additional perspective and enrichment. No matter how large a company is, its own data footprint is a tiny proportion of the footprint available across all the organizations in the world. Understanding a sector, market or particular phenomenon will often require data from many sources including their own.

Taking a topical example, how many organizations have been able to adequately assess the impact of COVID-19 by simply looking at their own data? They may have an insight into what their employees, existing customers, and direct suppliers are doing, but understanding how a given community, supply chain, sector, or jurisdiction has been affected requires more data. Ironically, the speed of COVID-19 and the sudden desire for data to understand and contextualize it unearthed a general failure on both the supply and demand side to quickly exchange and collaborate on data.

As explored in Solving the 80/20 Data Dilemma, the ability to exchange and collaborate on data within and between large organizations has become a core competency for every data-driven organization. This need is being compounded by the need to fuel data-intensive technologies, such as machine learning, intelligent automation, and artificial intelligence. Concurrently, the supply of new data has been accelerating dramatically in line with digital transformation, something that itself has itself accelerated dramatically over the last six months. 

Despite this, many organizations still struggle to optimize their interaction with third-party data. Sourcing is skewed to established providers that can be challenging to navigate due to their size and scale. Slow, manual assessment processes based on samples lead to imperfect results and imperfect decisions. Laborious contract and pricing negotiations bring little or no repeatability. Organizations invest a tremendous amount of effort refining and integrating data to deliver value with little or no re-use of that work.

It is now an opportune moment for large organizations to take a fresh look at their capability to source, assess, acquire, and use third-party data. Are their people, processes, and technologies sufficiently prepared for the speed at which the supply and demand for data is changing? Processes will need to be highly scalable. The reliance on manual work will need to reduce. Duplication must be avoided. 

Underpinning much of an organization’s capability, the focus on third-party data is only likely to increase in line with the expectations surrounding the ability to extract value from data. The following strategies offer practical guidance for those looking to gain a competitive advantage, whether through general improvements or by pioneering a fundamentally different approach.

Authored by Anthony Cosgrove (Co-Founder) at Harbr