95% of organisations suffer from the data decision gap, as highlighted in the findings of the first-ever Data in Context study; an independent report conducted by Quantexa.
The independent report is based on interviews with 750 IT and data decision-makers in the Financial Services, Insurance and Public sectors, across three continents.
A data decision gap is the inability to bring together the internal and external data needed to make accurate and trusted decisions. This is largely down to incomplete datasets, which ultimately impact the bottom line.
The top three effects of this are:
- Regulatory scrutiny and compliance issues (47%)
- Missed customer experience opportunities and retention problems (44%)
- Resource drainage due to increased manual data workload (42%)
Strategic and operational decisions inevitably suffer when based on a poor and incomplete picture. The study found that concerningly, 50% of strategic decisions are missing crucial intelligence because organisations can’t take full advantage of data. Only slightly better for operational decisions, just 52% manage to rely on data.
The Three Biggest Problems: Data Foundation, Contextual Analysis, Automation
Firstly, organisations typically struggle with establishing an enterprise-wide, reliable data fabric as the foundation to effective decision-making.
Secondly, that data needs to be connected to create the relationship view that is crucial to managing everything from enterprise risk through to customer experience. Without this, organisations will struggle to identify emerging patterns from real-life entities.
For example, uncovering the real beneficiaries behind offshore companies, detecting fraudulent credit applications, and discovering buying patterns that convert shoppers into long-term loyal customers.
The data decision gap is growing fast. The installed base of enterprise storage is growing at an annualised growth rate of 31%, totaling 5,451 exabytes (EB) in 2025 according to IDC.
If the data foundation is disjointed and incomplete, analytic models will be inaccurate whilst lacking explainability.
Even when an organisation solves the issues around analysing data in context accurately, the question becomes how to do it at scale.
The answer, as Quantexa suggests, lies in decision automation.
As exposed in the research, a mere 14% have successfully implemented automation initiatives in operational decisions, while 9% have yet to even begin the journey.
The 77% that are currently somewhere in the automation journey face a series of challenges, including:
- Decision-making inaccuracies (39%)
- Lack of trust due to a lack of explainability (38%)
Overall, the inability to see data in context, analyse it for trusted decision making, and automate it at scale, add up to the data decision gap.
Vishal Marria, CEO and founder of Quantexa, said: “The pandemic put data in the spotlight. Digitisation has meant organisations face an increasing tsunami of data, and many 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 (CDI) turns traditional data approaches on their head, connecting each datapoint 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 (AI), organisations can scale automated decisions across the business, freeing humans.”
