By Ashley Kramer, Chief Product & Marketing Officer, Sisense
The Business Intelligence and Analytics market is entering a new generation. Analytics have come a long way over the past few decades, starting from “Gen One” BI, with on-premises data and heavy IT-driven reporting projects, which was burdensome for both IT teams and end users. While cumbersome and requiring heavy investments, a few enterprise organizations reaped big benefits and it lit the spark for analytics.
Next, we entered into the era of data democratization or “Gen Two” BI which focused on making data more consumable, easy to use and accessible by putting the power into the hands of the business. While organizations gave out more licenses there was a fundamental flaw which required people to change the way they work, getting out of their normal workflows to find a dashboard to leverage data. This second generation brought greater success for organizations yet only business adoption of Big Data continues to be a struggle, with 73.4% of firms citing this as an ongoing challenge. (source: NewVantage Partners 2020 Big Data and AI Executive Survey).
So far, each generation only incrementally improves upon the past generation, not unlike the advent of the iPhone. There were smartphones before the iPhone, but they didn’t offer the same user experience.
We are now on the cusp of “Gen Three” BI, ushering in the Age of Action. This offers a new, agile way of using AI and analytics for every decision. Like the invention of the steam-engine, I expect this to usher in a revolution for how we drive business innovation.
Taking action on real-time intelligence
It’s estimated that the average adult makes 35,000 decisions a day (reported by Psychology Today). As consumers, we rely on and expect updates in real-time so we can make better-informed decisions. We turn to our smart devices to get insights into everything from weather and stocks to wait times for airport security and emergency rooms.
In business, our employees, partners and customers also make decisions every day that impact the bottom line so why wouldn’t we expect the same level of insight at work? In the Age of Action, insights arising from analytics and AI are no longer a luxury, but a necessity for achieving competitiveness whether in employee or customer-facing apps and workflows.
What’s holding businesses back?
Organizations have clearly defined the business outcomes they need to achieve and according to IDC’s Data Strategy Survey, more than half of organizations look to improve efficiency by using BI and analytics. Fifty-two percent of software companies and 50 percent of finance companies use BI and analytics to identify new revenue streams which is key to growing the business.
So, what’s keeping businesses from moving into “Gen Three” of BI to achieve those outcomes?
The chief obstacles to achieving more business value, according to the Harvard Business Review Analytic Services Pulse Survey for Sisense, are lack of skills/training, lack of quality data, and company culture, cited by 61%, 43%, and 24% of respondents, respectively.
Despite a recognition that they need to be “data-driven,” organizations are incrementally improving their data and analytics process yet expecting a next generation result. While most companies try to upskill their employees with training or other resources, this is not reducing the learning curve for most users. Organizations should leverage the power of AI technology to do the heavy lifting, automatically highlighting insights and explaining what is happening in the data so that anyone, regardless of their familiarity with data, can make sense of and take action with intelligence-informed decisions.
Making data accessible
Data is also often not easily accessible for the teams who will most effectively take action on it. According to the Harvard Business Review Analytic Services Pulse Survey for Sisense, only a small percentage (14%) of respondents say analytics are built into nearly all of their tools and workflows to help reduce the analytics adoption gap. Embedding actionable intelligence into business applications that can automate multiple steps in a company’s existing workflow will drive better business outcomes without users having to leave their primary tasks to look for answers in the data..
Savvy companies are finding ways to infuse insights into their workers’ daily tasks, allowing them to seamlessly make decisions within a business application. Additionally, these same companies are integrating insights and analytics into their customer-facing products to increase stickiness and even drive new revenue. By bringing data to the people, with the right levels of governance and security, the friction throughout the entire data lifecycle is removed and an intelligence-informed culture is created by infusing, not forcing, data into everyday decisions.
Companies taking action
DNV, an assurance and risk management company, is generating new subscription revenue by embedding an analytics platform for utility companies. This platform, “Cascade Insight,” helps their customers get ahead of maintenance issues and avoid service outages in their grid, ultimately saving money and delivering better value and service to utility companies.
Another example is GE, which uses an application called GE Smart Scheduling across more than 150 hospitals to predict no shows and cancellations for MRI and CT scans. With Smart Scheduling, one imaging center in Chattanooga increased revenue by $100,000 per year by decreasing no shows and cancellations, while increasing care to their patients, communities and optimizing machine usage.
Tessitura Network, a non-profit software company uses its enterprise application, Tessitura Analytics, to deliver actionable intelligence to over 650 performing arts and cultural organizations. Using APIs, customers can extend and customize insights to improve their fundraising, ticket sales, and inventory. During COVID-19, Tessitura helped arts and cultural institutions assess reduced capacity seating options in live venues as well as how to analyze and manage canceled events.
Flipping the script on analytics
Data is a critical asset and competitive advantage that most organizations are still not able to use fully if they follow the incremental improvements of the past. Innovative use of AI and ML methods in all fields will accelerate this advantage, but by flipping the script on analytics adoption and infusing actionable intelligence wherever people spend their time, organizations can go beyond standard dashboards to automating steps within existing workflows.