It is becoming painfully apparent that traditional dashboards are too slow and static to compete in our changing world. While COVID-19 has driven the point home, there are more changes to come that will be demanding faster and more innovative solutions for competitive decisions. Traditional dashboards fail to deliver on the data-driven culture as data speeds up and sits in the cloud for new AI and advanced analytic assisted decisioning. According to the Harvard Business Review in 2020, 84% of frontline workers report a poor experience with today's analytical solutions, and 67% of executives are not comfortable using data from their existing data resources. It implies that the problem with decisioning is that there is more than keeping up with known or emergent KPIs.
The Need for Speed
Traditional dashboards do not deliver modern world speed because they are fragile and use old data. Most decision-makers are dealing with data that is 4-5 business days old at best. If a decision-maker wants a new insight or tries another decision-making approach, it takes too long to change the existing dashboard. The data is slow; the dashboard changes are time-consuming and expensive. It is no wonder only a small group of executives believe their existing analytic solutions are mature enough to keep up with the organization. Faster decision data in the cloud is one step in the right direction.
The Need for Complete Context
It is so easy to focus on fragments of a decision and sub-optimize. Often getting data about critical neighboring contexts and downstream impacts of decisions are overlooked, or the time-pressure causes this step to be skipped. Often siloed analysis contributes to a fragmented insight situation. It can be caused by organizational boundaries, various tools, and incomplete data sources. Therefore organizations are moving from a patchwork of disconnected dashboards to management cockpits.
The Need for Collaboration
A wise decision-maker will often check with other fine minds and experience bases to attain decision excellence. Collaboration alone can help knock down some of the organizational walls and resist a significant decision, and take appropriate actions with speed. It is beneficial in verifying the data and the potential downstream outcomes of a decision and the resulting actions/impacts. Often the collaboration tools are devoid of decision contexts and are a separate disconnected toolset.
The Need for More Smarts
Even these fast boards need assistance with detecting necessary signals, events, and patterns. It is mainly an issue for emergent situations where the signals, tolerances, and patterns were not anticipated. Since there is no way for the human eye to catch these speedy emergent patterns, there is a crying need for AI and Analytics with insights to detect these patterns in real-time minimally and predict the emergent trends ideally. These same smarts will help us personalize the analytic outcomes and new fast bords that play in a management cockpit.
The Need for Dynamic Experimentation
Once detected, the decision-maker can orient his/her options with the help of collaborators. Some of these collaborators should be AI and advanced analytical models that can project the impact of a decision and resulting changes. The ability to experiment with a range of analytics producing various outcomes is a must in a world of increasing speed. It may imply re-using models and analytics that have proven helpful in the past. All of these contribute to an immediate use-case development environment. In today’s market only a few players seem to understand what decision-makers want including SAS, Tibco, ThoughtSpot, and Wizly
The tension between dynamic data and static siloed dashboards has to be resolved in a world of change. We are no longer in a steady-state, and I expect more issues to respond to with fast boards applied most intelligently. If we can’t do that, we will never scratch the surface of all the big and complicated data we are capturing today and storing for tomorrow. It’s time to modernize decision-making to help optimize operational outcomes while sharpening organizational tactics within emerging opportunities and threats that may deliver new strategies.