3 Steps to improve your Decision-Making process

3 Steps to improve your Decision-Making process

The ability to make high quality decision is central to any organization. The expansion of the volume, variety, and velocity of information make this ability increasingly difficult. With the state of current data explosion, decision-makers have to respond more quickly and with greater precision than ever.

To improve your decision-making process you should be considering the following:

  1. Do not focus exclusively on historical experience Traditionally, decisions have been made on the basis of anecdotal experience of domain experts. These decisions are subjective and often inconsistent, thereby limiting their value for the organizations.
  2. Business rule tools become obsolete quickly Having the need to standardize key decisions and make them more consistent and reliable, many organizations have moved toward automated decision-making by using business rules. Although this automation provides a degree of efficiency and objective consistency, and improves the collective quality of decisions, static rules quickly quickly become obsolete in ever-changing situations and conditions, and the limits of this approach become apparent.
  3. Predict for specific conditions rather than for generalizations: Predictive decision-making, based on analysis of historical patterns and current conditions, is the basis for the highest quality means of making decisions. The reasons are because the models consider all available data, and also continuously adapt to new information, becoming smarter over time. With predictive analytics, the right decision for the given conditions can be made at the point of impact at the time when the decision needs to be made. Decisions are now customized for each unique case, rather than using generalizations for the aggregate.

Predictive Analytics tools can generate extremely useful insights and actionable predictions that will improve the decision-making process by doing it less anecdotical, less obsolete, and more relevant to the problem to solve.

Predictive Analytics-as-a-Service

Murali recently joined our team as CTO and he has been helping Predikto with our messaging. He suggested we use the term Data Scientists-as-a-Service. I liked that idea and it morphed into Analytics-as-a-Service. Any solution, capability, or software enabled service can be delivered more efficiently through the cloud as an “as-a-Service” offering. This is exactly what Predikto is all about.

We want to shield our customers from complex technical jargon, statistical complexities and nuances, architectures and databases, and much more. We are all about enabling our clients to perform an action that impacts their bottom line. We enable this action by delivering Predictive Analytics solutions through a Cloud based service offering. Our deployments take a fraction of the cost and time of trying to do them on their own. This is the future of technology enabled solutions for the enterprise.