2. Insights orchestration: integrating and expanding
If employees are acting on insight in silos, those actions have limited value. For example, effective changes made to a marketing strategy based on customer insight analytics could also be made to a sales strategy. Therefore, employees must share what they learn with other business functions. To achieve this, data visibility must increase across the enterprise.
Migrating analytics to the cloud: InterNex Capital, an asset-based digital lender, wanted to develop a new cloud-based digital lending solution. Today, the solution allows employees to harness the power of artificial intelligence (AI) and predictive analytics to determine the likelihood of fraud or payment default across its customer base. In this example, connected customer analytics gives employees the ability to make more informed decisions at speed.
3. Self-service capabilities: empowering every employee
When time is money, the faster employees can act on insight the better. When you empower different business users and teams to perform bespoke analysis using self-service capabilities, they don't have to wait for the insights to come to them – they can seek them out. This enables employees to act with agility to achieve business objectives.
Taking decisive action during uncertain times: During the COVID-19 pandemic, care managers at a private health insurance company needed to support members at the highest risk of suffering complications if they contracted the virus. Dashboards with self-service capabilities enabled care managers to identify high-risk members by location, medical history, and profession to proactively connect with those members and offer guidance on available resources.
4. Interaction engineering: putting experience at the heart of analytics
Ensuring all employees can act on insight requires analytics solutions that are user-friendly and intuitive. By applying interaction engineering principles, you can deliver intuitive, seamless, and personalized solutions. These solutions should offer features that enable collaboration across teams and business units – like allowing users to tag other users on relevant insights – to expand the reach of actionable insights.
One-stop shop for analytics: A global beverage manufacturer needed a comprehensive analytics solution. Using an advanced visualization engine embedded with data science, data engineering, AI, and machine learning capabilities, the solution collated insights on supply chain management, working capital and accounts payable optimization, and customer experience strategy. The solution gave employees the ability to act on insight and share knowledge at speed. This led to a 5x increase in the use of analytics to transform customer experiences, develop more efficient processes, and control costs across the enterprise.