A more human approach to data can achieve Active Intelligence

The potential of data has always been clear – but that doesn’t mean that it is easy to harness

Even with the recent trend in “self-service” to empower data use, our research with Accenture revealed that less than one in five (18%) organizations give everyone access to tools that are appropriate to their skill level.

This has been a consistent issue with second-generation business intelligence (BI) software. While many of these applications were intended to be put into the hands of business users, most remain passive and rely on the knowledge and experience of the user to be able to find valuable insights for decision-making. With low data literacy skills among employees (21% globally), and just one-quarter (25%) fully prepared to use data when entering their role, this has resulted in a workforce that avoids using data (36%) or the task entirely (14%) because it feels so overwhelming.

The true potential for business users will only be unlocked by enriching the process of generating insights from data. The market must shift to provide more intuitive services that proactively serve the information users need, while prompting them to take actions based on the insights.

Relevant data must stop being something you need to discover. It must become something that you are served when you need it in the business moment. But how can we shift people away from a passive experience of analytics to achieve Active Intelligence?

Create personalized data experiences

It is too much to expect of business users to constantly sift through data to find what they need to make informed decisions. When data isn’t your ‘day job’, finding the time to do this can fall to the bottom of the list. Instead, business users need to be able to easily create a one-stop shop of the metrics that are relevant to them, that they can then interact with and track in real time.

While some second-generation tools do offer customizable dashboards, the set-up process often requires a greater understanding of data and the platform than most business users have. When the process is not accessible, organizations are caught in a catch-22 and the value of the platform is likely to be limited. If the responsibility falls on the business user to identify and introduce the most relevant information, potential insights are easily missed. Equally, this same outcome can arise when the process is centralized by BI teams. While overcoming the skills gap, they are not subject matter experts, and therefore will not naturally know all the relevant questions the user may want the dashboard to ask.

Leveraging maturing technologies, such as natural language understanding, to allow users to easily navigate vast data sources to find what they need to build their personalized dashboard will finally put the power in hands of subject matter experts if the data used by these augmented analytics experiences are analytics ready and governed.

Inspire users to act

The potential of data is not in having access to it, but in the decisions and actions that are taken from the learnings it provides. By taking a personalized approach to data analysis, it is now possible to use cognitive engines to turn insights into recommended actions that can easily be taken through software integrations.

So, what does this look like in real life? Let us take a sales manager, for example. They can be informed via email of changes to Salesforce data and have a predefined action of replenishing an order offered. This empowers the manager to merely approve the proactive suggestion determined by the cognitive engine, rather than requiring them to go into the data, determine the state of the company’s inventory and from there judge whether a new order is needed. In this scenario, cognitive engine is supported by intelligent data analytics pipeline with CDC and active data lineage so that it knows all of the changes happening in the data generating real time contextual insights triggering actions. With this approach, users not only gain personalized, real-time insights from changes that are happening in the data, but also have an Active Intelligence system that empowers them to take fast, informed decisions.

Make data decision-making processes collaborative

When organizations achieve a culture of data-driven decision-making, the process is never linear and rarely a solo expedition. The data becomes an integral part of our discussions, and to truly collaborate we must not only communicate what we believe the outcome should be, but also the context which informed that thinking. Being able to share our data workspace with others allows them to understand the journey we’ve taken through the data and how that has led to the insights we’ve produced. Making data exploration part of team discussions enables us to finally put data at the heart of our collaborative decision-making.

Helping data serve the business

The greatest hurdle that many organizations are currently facing is how to make their vision of a data-driven workforce a reality. There are undoubtedly three key elements here, as with any successful technology adoption – a trifactor of people, process, and technology. While the potential to improve their own processes and upskill their workforce lay in the hands of business leaders, for too long these ambitions have been held back by solutions that are not intelligent enough to truly serve the business user. Now, as we enter the third generation of BI, the promise of achieving Active Intelligence is finally in sight.


About the Author

Elif Tutuk is VP of Qlik Innovation and Design at Qlik. Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. Qlik provides an end-to-end, real-time data integration and analytics cloud platform to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships.

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