Cultivating a data-driven culture and fully embracing advanced analytics is no small feat for corporations, and implementing prescriptive analytics is no exception. It requires significant investment, expertise and total buy-in from every department and team, and it's just as true for businesses that have achieved some measure of data & analytics adoption and success as it is for those just starting out on their analytics journey.
For those more sophisticated, data-driven corporations, the issue of total commitment often rears its head when attempting to take the next evolutionary leap into prescriptive analytics. Time and again, internal dynamics and inertia create roadblocks to prescriptive analytics execution, and prevent businesses from achieving analytical maturity. To overcome these hurdles, prescriptive analytics evangelists need to work with department heads and other key decision-makers to foster top-down commitment to their cause and get complete business buy-in.
Why demand for prescriptive analytics continues to rise
Prescriptive analytics can be thought of as the culmination of the big data movement. Where descriptive analytics will tell you what has happened, and predictive analytics can tell you what may happen, prescriptive analytics tells you how to capitalize on that information and make decisions that put your business in the best possible position to succeed.
"The potential of prescriptive analytics is tremendous."
Prescriptive analytics enables businesses to see the potential outcomes resulting from the choices they make today, allowing them to make operational decisions that maximize business efficiency. The potential here is tremendous, and it's no surprise that Global Industry Analysts predict the worldwide prescriptive analytics market to be worth $1.6 billion by 2022.
How internal dynamics get in the way
Any time businesses leverage prescriptive analytics to make potentially drastic operational changes, there's a chance that the right business decision won't completely align with the goals of individual departments, teams or employees.
Under these circumstances, a prescriptive analytics project as seemingly straightforward as optimizing supply chain operations could become very difficult to execute. For instance, an optimization model may suggest that the most efficient and fiscally prudent tactic is to let inventory amass at supply centers until they reach a certain threshold before shipping all of these products at once.
However, that approach may not align with the goals and incentives of warehouse or supply managers whose job performance has been historically judged in part by how quickly inventory moves through their facilities and reaches its destination. They may also chafe at the idea of ignoring their own experience and professional opinions on how to best manage supply chain operations.
The end result is a supply management team that is skeptical of the data insights and its subsequent optimization modeling, leading to a credibility gap that causes internal friction and damages morale among stakeholders who will prove essential for implementing the improved, data-driven approach to supply chain operations.
Why executive buy-in is key
This fundamental disagreement of data versus experience will be difficult to reconcile without a more widespread commitment to prescriptive analytics. Any dissent can create fissures in a company's nascent data-driven culture. By having the support of the corporate brass, data analytics advocates can overcome these obstacles and put their prescriptive analytics results into action.
Going back to our earlier supply chain example, supply managers are unlikely to feel compelled to change the way they operate - especially if those changes seem disruptive to current workflows or difficult to implement - without encouragement from above. Ultimately, those prescriptive data initiatives will fail, despite the best efforts of internal analytics supporters.
When prescriptive analytics efforts have the full backing of corporate leadership, however, those same supply managers will be obligated to enact difficult process changes for the ultimate benefit of the organization. In this way, organizational inertia can be overcome, and prescriptive analytics projects can be given the chance to really flourish.
Businesses cannot half-heartedly embrace prescriptive analytics. They need to be prepared for those projects to potentially bring uncomfortable truths to light and enact changes that could upend the natural order of enterprise operations.
Any successful implementation of prescriptive analytics will have the full support of the executive team, so it's essential that the foundation has been laid before diving too deep into an analytics project. A data & analytics consultant can help bridge the gap between operational perception and reality, leveraging their experience and track record of success in this field to foster corporate buy-in and cultivate a more data-driven organization. With that expert-level assistance, you can be sure that your analytics projects deliver not just insights, but tangible results, as well. For questions on how Clarity can help you implement prescriptive analytics, Contact Us.