Nine in ten global organizations struggle with data despite increased focus during pandemic, research finds.
The study, conducted by data and analytics firm, Quantexa, comprised interviews with 750 IT and data decision-makers in Financial Services, Insurance and Public sectors across three continents.
Results showed that the overwhelming majority (95%) of organisations suffer from the “data decision gap” – the inability to bring together the internal and external data needed to make accurate and trusted decisions.
This is due to inaccurate and incomplete datasets, which ultimately impact the bottom line. The phenomenon leads to missed opportunities to enhance customer experience, and loss of resources through increased manual data workload.
Inevitably, strategic and operational decisions suffer when they are based on a poor and incomplete picture. The study finds half 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.
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,” Vishal Marria added.
The problems: data foundation, contextual analysis, and automation
Organisations typically struggle firstly with establishing an enterprise-wide 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 can’t spot 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 annualized growth rate of 31%, totalling 5,451 exabytes (EB) in 2025 according to IDC. If the data foundation is disjointed and incomplete, analytic models are inaccurate and lack 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 is automating decisions: The research discovered just 14% have already implemented successful automation initiatives in operational decisions, while 9% have yet to start the journey.
The majority, 77%, are somewhere in the automation journey, and facing key challenges. Nearly two in five, 39%, struggle with inaccuracies in decision-making. A further 38% of the total do not fully trust those decisions due to the lack of explainability.
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.
Contextual Decision Intelligence (CDI)
Vishal Marria continued:
“Contextual Decision Intelligence (CDI) turns traditional data approaches on their head, connecting each datapoint to all others in the organization 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), organizations can scale automated decisions across the business, freeing humans,” Vishal Marria added.