'Slow' humans cause firms to suffer 'data decision gap'

Companies’ attempts to bring together the internal and external data needed to make accurate and trusted decisions are being hampered by the very people who in charge of the process, with 95% of European organisations crippled by a “data decision gap”.

So says a new new study by global data and analytics software company Quantexa, which quizzed nearly 350 technology and data decision-makers across financial services, insurance and the public sector in the UK, France, Netherlands and Spain, and found there simply are not enough hours in the day for humans to complete these tasks.

According to the findings, the real cause for concern is that this leads to inaccurate and incomplete datasets, which ultimately have a negative impact on businesses’ bottom line.

More than two-fifths (43%) of chiefs reckon the “data decision gap” can also trigger regulatory scrutiny and compliance issues, with a similar proportion (42%), citing customer experience opportunities and retention problems, and (42%) resource drainage due to increased manual data workload.

Strategic and operational decisions also suffer when they are derived from poor, incomplete pictures that lack context, with the study revealing that one in every two strategic and operational decisions does not take full advantage of the organisation’s data.

The report also delves into the three most impactful data issues for European businesses: data foundation, contextual analysis and automation.

Firstly, organisations typically struggle with establishing an enterprise-wide data fabric as the foundation to implement effective decision making, the report claims.

And, with IDC forecasting that the installed base of enterprise storage is growing at an annualised rate of 31%, totalling 5,451 exabytes (EB) in 2025, if the data foundation is disjointed and incomplete, analytic models will become increasingly inaccurate and lack explainability.

Secondly, that data needs to be connected to create an overarching relationship to manage everything from enterprise risk through to customer experience. Without this, organisations cannot spot emerging patterns from real-life entities.

For example, uncovering the real beneficiaries behind offshore companies, detecting fraudulent credit applications, or even discovering buying patterns that convert shoppers into long-term loyal customers.

Even when an organisation solves its issues surrounding contextual data analysis, the next question becomes how to do it at scale.

Quantexa’s reckons the answer is automating decisions yet just 13% of respondents to this survey have implemented successful automation initiatives in operational decisions, while 10% are yet to start the journey.

As a result of needing to capitalise on their data, many organisations (50%) are looking to incorporate modern entity resolution technology like contextual decision intelligence (CDI), with 49% wanting to drive improvements in master data quality overall.

Quantexa chief executive and founder Vishal Marria said: “The pandemic has put data in the spotlight. Digitisation has meant organisations face a tsunami of data, and many have found they couldn’t take strategic advantage of the opportunity that connected data brings.

“Today’s organisations have all the data assets they need to make better decisions, but the data decision gap means they can’t extract meaning or value out of their data, as they can’t connect it to generate the single, accurate view needed.

“Contextual decision intelligence turns traditional data approaches on their head, connecting each data point to all others in the organisation and external data sources. With this connected basis, decision makers can see a single view of customers, from which they can extract real-world intelligence and take action. Then, with the addition of artificial intelligence, organisations can scale automated decisions across the business, freeing humans.”