Successful businesses require an effective data strategy. While some organisations may manage, store and integrate data efficiently, most are unable to add the context needed to make accurate data-driven decisions. As data is being generated at an unprecedented rate, it is becoming increasingly cluttered and harder to derive value from. Many businesses focus on collecting data, but more data can simply equal more problems if the organisation does not have the ability to drive actionable value from it. Accurate business decisions can only be made where the full context around the data is understood. This context is what ultimately unlocks the true value of the data.
The data decision gap and how to overcome it
To know if someone’s likely to buy a product, a retailer needs to know what else they’ve bought so they can put in front of the customer something they are likely to like. To know if someone is laundering money, the bank needs to know where else that money has been. The problem is, despite carrying out massive infrastructure investments, legacy-burdened organisations are sitting on mountains of data and struggling to extract meaning from it.
Whilst these data assets languish in silos and data lakes, failing to prove value, operational staff get a one-dimensional view, full of false positives and negatives that slow them down. Siloed data makes it impossible to see the full picture — which leads to inaccurate decision-making. This is the data-decision gap and it is choking the value out of enterprise data assets.
To gain insights from the raw data, organisations must combine their data sources in some way within the data lake. They need to create a single view of their data records, which is where many organisations struggle. The first key to these data lake challenges is to find the connections between your records and join the ones that are the same and bridge the data decision gap.
Real-time data analytics and the value of continuous actionable intelligence
Big data means big decisions
Data is key in disentangling the problems companies need to solve and aiding the decisions they need to make, but for that to happen, the data decision gap needs to be overcome. The only way to bridge it is to make data more meaningful with context. For data management professionals, everything needs to be viewed within the context of business agility; they need to be able to look at all of the technical data and instantly understand what it means, in order to extract insights which will help avoid risks and discover new opportunities.
Contextual decision intelligence (CDI) is the best way to turn all internal and external data sources into context for every single operational decision. To reveal the bigger picture, CDI creates a single repository that scales across the business and dynamically tailors connected views of data to multiple cases.
The foundation of CDI is dynamic entity resolution, a tool which stitches together disparate data points from multiple systems into an accurate single view. This helps organisations spend less time gathering data and controlling its quality. Instead, they can focus on building the contextual foundation which then enables them to drive better decision-making across the customer lifecycle, uncover hidden risk, and discover new unexpected opportunities.
Network generation then connects established individuals to a network or graph, and reveals hidden connections between individuals, organisations and events. This dynamic, graphical view of the bigger picture, automatically compiles the most relevant connections, entities and data to inform decisioning.
The technology powering CDI, such as entity resolution and graph analytics, allows systems to make associations between applications, accounts and people that otherwise would have gone unnoticed. These flexible and transparent analytical models, based on intuitive features and patterns, give companies the confidence to automate decision-making.
Making data meaningful
Contextual decision intelligence changes the way organisations do business by closing the data decision gap. The continuum of context, when related to data, can lead to new information, insight, decisions and ultimately action. By implementing data and analytics capabilities that are designed to provide context, you are able to learn more about your customers and design the appropriate processes that will attract similar potential clients or reduce the losses associated with risks and threats. The pay off? Your organisation has made its data meaningful to process millions of trusted operational decisions more accurately.