Members Spotlight: HARNESS Property Intelligence

Members Spotlight: HARNESS Property Intelligence

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We spoke with Ben Mein, CEO of HARNESS Property Intelligence, a new on-demand approach in harmonising and evaluating commercial property data to enable you to release value through data science and machine learning.

Ben discusses the future of data usage in the property industry, the problem HARNESS are solving and shares insights into their innovational development at HARNESS.

HARNESS evaluates commercial property data, can you give us an insight into what this entails? What problem are you trying to solve?

The technology we’ve developed enables organisations to unlock their data for competitive advantage. Essentially we’re specialists in data enablement – turning unstructured data into structured so that businesses are able to commercialise it better.

Companies have a vast array of commercial real estate intelligence siloed in multiple formats across their organisations that they need to make sense of. We’ve built a platform that can programmatically extract, cleanse and structure these disparate data sets from across an organisation, creating a unified “single property view” data set able to feed back into their internal systems. Through the fusion of data sets, the platform is able to deliver far more advanced coverage and granularity of property stock than is possible with more standard data aggregation.

What are your views on the future of data usage in real estate?

An organisation’s proprietary data is a key competitive advantage, and therefore sharing that externally without knowing the beneficiaries represents a complex challenge for business leaders. Data sharing tends to best serve a company’s interests if done on a reciprocal arrangement, where all parties can benefit strategically and commercially. The time a data set should be syndicated and made available to all parties is when it ceases to be a key driver of an organisation’s competitive advantage, but at least still contributes value to all parties.

Data sets will continue to be commoditised, but only as their unit value lowers in the market. This will likely be driven by surges in higher value information from new sources, which will remain proprietary. This is constantly evolving as data moves.

How do you see technology evolving in your company?

We’ve cracked some of the hardest technical challenges in data extraction and fusion, creating significant coverage and granularity advantages in the fabric of commercial real estate data. We anticipate this will cross into other industries ancillary to CRE, however our key focus is on ensuring what we’ve already developed is enhanced and advances.

Can you share with us any innovational developments at HARNESS?

We’ve demonstrated to a number of CRE players that we’re able to deliver advanced PDF extraction in a live environment, including on documents with tables and complex tenancy schedules. The feedback we received at the time was that no one else has been able to accurately extract data from these types of challenging PDFs, although we’re still learning – or at least “the machine” is. However our most innovative development has been our proprietary address matching solution that provides 25% greater coverage of commercial real estate stock than UPRN alone. As we go far beyond UPRN, we have developed a HARNESS property identifier (HPID) as a unique index solution in order to reference the additional CRE stock. These solutions are foundational, the rest is top secret.

Lastly, where do you see the industry headed in 2-5 years time?

As with any industry undergoing a period of maturing digital transformation, there will be greater openness of CRE companies to working with data and tech specialist vendors, rather than trying to build entire tech programmes in-house. Sadly, this will only happen once significant budgets and time has been burned in-house; having previously witnessed this in large organisations it is far riskier than using an external partner. Furthermore, while there will naturally be some consolidation amongst existing tech players, I also predict an increase in the number of technology companies producing game changing innovations. This pattern has been demonstrated already by other industries that are ahead in digital transformation, like advertising, media, finance, and healthcare.


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