Three critical components to generate value from Prescriptive Analytics

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Three critical components to generate value from Prescriptive Analytics

Prescriptive Analytics (PA)1 is widely used to forecast future events by leveraging Big Data, Artificial Intelligence, and several other sources of information. These forecasts provide companies with tangible insights that can transform the way it does business. But how much are the insights worth and how do companies ensure they translate to dollars?

At PIP, we work with clients to ensure Prescriptive Analytics generates tangible new insights that impact a businesses’ bottom line. Our experience has shown companies have the potential to achieve an additional 10-20% of value from current operating and maintenance practices. So, what’s the catch? Big data or Prescriptive data analysis by itself, too often produces relatively low value or even misleading insights. Without the necessary process and behavioral changes, the potential is not secured and locked in on the front line.

How, then, can we ensure Prescriptive Analytics generates maximum value? At sites, the biggest roadblock we see is that companies are simply trying to implement a shiny new tool and have little clarity on how much value the initiative can provide. To steer results in the right direction, we implement three critical components:

1. Find the most valuable levers by upfront prioritization – Surpass the temptation to interrogate data ‘because it is there’ and focus on the areas that create maximum value for the broader operations. Correctly focused insights will help create value quicker.

2. Use a cross-functional team to ensure the insights are actionable – Output from data analytics is not always immediately actionable. It is essential to establish a team which can solve the problem, this should include experts from within the business who understand the operations, as well as data scientists who are able to help draw conclusions from large sets of data through interactions with the Subject Matter Experts (SMEs).

3. Adapt business practices to embed data analysis – Data analytics can help identify when issues arise, but this information needs to be readily available to the team and they need to know what to do with the information provided. This includes users challenging existing business practices so that acquiring data, monitoring results, and setting actions seamlessly integrates with everyday operations.

How much value has Prescriptive Analytics generated your business? What steps have you taken to ensure success? What challenges are you facing?

1. Prescriptive is not enough to provide actionable recommendations. Prescriptive provides operational recommendations to drive desired outcomes and accelerate results.