From Data and Analytics Experts and Academics
Recently, Axis Group and Darla Moore School of Business brought together industry experts, academics, and data and analytics practitioners for the Analytics Think Tank Roundtable. The group explored questions about evolving from business intelligence (BI) towards augmented/artificial intelligence (AI) and continuous intelligence (CI). Read on to learn the conclusions they came to.
AI, BI, and CI can co-exist.
Just because you are adding AI and CI into your organization does not mean that BI goes away. The data visualization, storytelling, and analytics used to drive business decisions may persist as they do today. Meanwhile, some teams and departments may also need more predictive, diagnostic and prescriptive capabilities that can only be delivered by AI and CI.
Prepare for CI using the DELTA framework.
The DELTA (Data, Enterprise, Leadership, Targets/Technology and Analysts/Analytics Techniques) framework was developed in 2010 by Tom Davenport, Jeanne Harris, and Bob Morison. For CI to become a reality, real-time data is of the utmost importance, which requires a focus on Data Ops. From an enterprise perspective, organizations must ensure their teams are ready to use data in their everyday decisions, which requires Enterprise Data Literacy. Also, leadership support is vital when considering a move to CI, as well as strategic targets and reliable technology. To bring it all together, creativity and trust must be leveraged in combination with data and analytics techniques to solve real-world problems in a timely manner.
Data governance is no longer optional.
Data governance is not just a nice-to-have capability. With analytics tools so readily accessible, it is easier than ever for anyone with some experience to create a dashboard. As a result, critical amounts of time are wasted reconciling numbers and rationalizing results. Having an agreed-upon framework sanctioned by the enterprise is a big hurdle but is necessary to deliver a data governance structure that will save time and resources in the long run.
Focus on hitting base-hits, not just home runs.
Knowing that you are not going to show up and immediately begin hitting home runs, like delivering a new model or new AI product, right away is important to remember. Success in AI and CI will come from the cumulative process of showing up every day and hitting base-hits by using tools that you know how to use, adding new skills and software over time, and by continuously improving data governance, data quality and reliability. The cumulative effect is powerful, and you will realize the value in the journey.
Listen AND learn.
Things cannot always be done as they have been done in the past, especially if you have new business goals and performance targets. Moving beyond BI is both a journey and an evolution. People and processes must be reoriented; new technologies must be implemented and adopted. Take part in the transformation, ask questions, stretch yourself and your team, and be prepared to learn a lot along the way.
Remember your V’s from Data & Analytics 101.
The sheer amount of data (volume), the different forms (variety) it comes in, the speed in which data moves from one format to another (velocity), the data quality and integrity plus being able to sift out the nuggets from the duds (veracity), and the life cycle of data before it loses its need (volatility), are all crucial to remember. Additionally, visualization, or being able to utilize charts or graphs to visualize large amounts of data, is more effective than spreadsheets filled with numbers and other details. Value is the endgame. If your organization is not getting value from data, then change is necessary.
Digital transformation takes a village to deliver.
To get the most out of analytics, there are a ton of jobs that must get done and a variety of roles across functions and business units. It is important to examine analytics’ team makeup and ensure that the right people are in the right places and positions to get work done in order to guarantee a successful transformation.
Interested in hearing from the participants directly? You can watch a replay of the Think Tank by clicking below.
If you have a topic idea for a future Analytics Think Tank Roundtable or want to volunteer as a speaker, panelist, or discussion leader for a future event, visit our Call for Speakers site.