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Prescriptive Analytics is Going Mainstream. Is your Organization Ready?

With rising supply chain complexity, organizations are racing to improve the pace and quality of decision-making. To do this, many are relying on prescriptive analytics. According to Gartner, 11% of mid and large-sized enterprises currently have some form of prescriptive analytics. This will grow to 37% by 2022. AIMMS has been in the market of prescriptive analytics (otherwise known as mathematical optimization) since 1989. We turned 30 this year. Let’s explore what’s changed in the last three decades and what your organization should consider when driving prescriptive analytics adoption.  

forecast_snapshot_prescriptive analytics
Source: Gartner, Forecast Snapshot: Prescriptive Analytics Software, Worldwide, 2019

According to Gartner, 11% of mid and large-sized enterprises currently have some form of prescriptive analytics. This will grow to 37% by 2022. – Tweet this

What’s driving prescriptive analytics adoption? 

Prescriptive analytics is a type of advanced analytics that optimizes decision-making by providing recommended actionPrescriptive Analytics platforms, as defined by Gartner, “primarily focus on creating optimization solutions,” providing “data prep, prescriptive model building, model management and model deployment in various business processes.”  Prescriptive Analytics can be applied to optimize tactical, strategic and operational decisions.  


More awareness and ease of use 

The use of these optimization techniques has been around for decades but has traditionally demanded expert skills. This is changing, as vendors are increasingly invested in making this technology more accessible for end users. At AIMMS, we recognized this trend several years ago. This ultimately led us to launch AIMMS PRO and AIMMS SC Navigator later on.  

With the launch of SC Navigator – a suite of configurable Apps for supply chain teams – we started a movement for supply chain self-enablement. Companies like ELIX Polymers and Fresenius Medical Care North America have chosen SC Navigator because it makes powerful prescriptive analytics accessible and allows them to quickly answer very specific questions about their business. In the case of ELIX Polymers, S&OP Navigator allows them to quickly simulate the impact of any problem on their volume and EBITDA and decide on the best course of action. They can do this within an hour, with the management team interactively reviewing scenarios during a meeting – an activity that would have previously taken them at least 24 hours with more cumbersome and less interactive tools.  

Before the launch of SC Navigator, we released AIMMS PRO, which also made it considerably easier for data science/OR teams to deploy solutions to end users, and we transitioned to the Cloud to minimize IT-related friction in technology adoption. Cloud-based platforms like ours have made the deployment of optimization models easier. As AIMMS’ COO, Jan Willem van Crevel, writes: “in the past, organizations were dependent on the prioritization, capacity and skills of their company’s IT departments” to deploy AIMMS-based models. The cloud significantly “un-ITs” the consumption of optimization and opens a world of possibilities when it comes to scalability. 

The cloud significantly “un-ITs” the consumption of optimization and opens a world of possibilities when it comes to scalability.Tweet this

More investment in data science 

While data science talent is scare, organizations today are also more willing to invest in these skills. As our partner at ORTEC, Frans van Helden, recalls: “Back in the day, the application of mathematics was known as OR. These days, it’s called data science and it’s gone from a niche practice to a must-have capability.” Nowadays, management teams know what data science is and they recognize that they can gain value from it. 

The number of industries applying optimization has also grown, even in markets where the use of optimization has not been as widespread. Brazil-based Volnei dos Santos, Technical Director at UniSoma, states: “until the beginning of the last decade, most of our projects focused on steel, pulp and paper, and animal production businesses. We started seeing a broader range of industries using optimization in the last ten years, like manufacturing, beverages, education, and more. Diversification has been the theme of the last decade.”  

New ways to digitally represent the supply chain 

It’s not just an increased awareness and accessible, cloud-based technology that’s driving the adoption of prescriptive analytics solutions. The tools of the past are simply not enough to deal with the quantity of data available today. In supply chain, teams have traditionally relied on spreadsheets to digitally represent their supply chain and make planning decisions, but they quickly run into limitations.  

Spreadsheets are prone to error. They don’t support robust optimization. Managing data across multiple spreadsheets quickly becomes unmanageable and results in version-control headaches. As a result, companies are looking for more advanced capabilities. It’s now possible to create a robust digital supply chain representation that captures assets, processes, machines, products, customers, transportation, costs, constraints, and geocodes and shares data across functions. These types of digital representations make it easier to deploy optimization and a whole range of technologies 

Prepare for adoption with a change management strategy  

Undeniably, making the change from spreadsheets to a digital representation with prescriptive analytics capabilities is a big step. Trying to optimize everything without looking at roles, responsibilities and processes does not work, as ORTEC’s Frans van Helden explains. “It’s important to keep the context of the organization in mind when building optimization solutions. Change management and cultural intricacies need to be taken into account.”  

Gartner recommends that organizations start by identifying the “pre-requisites for success, ranging from organizational buy-in to redesign of current processes.” Ensuring the availability and readiness of data and internal skill sets is also key.  

Our partner Jack Pool, Managing Director at Districonrecommends that you train your end users in the use of the solution and work with partners that help you build trust in the technology internally. UniSoma’s Volnei dos Santos also stresses the importance of training and engaging key stakeholders early on with your optimization initiatives. This does not only streamline adoption from a change management point of view but also facilitates data collection and orchestration. 

Eager to learn more about prescriptive analytics? 

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