Resource utilization with decision intelligence

The pandemic has led to a global shortage of several commodities. Business and non-profit organizations alike face a scarcity of resources that is disrupting their operations. Supply chains across the world are still being restored. The need for optimization of resources is more pronounced than ever. While organizations cannot control the demand and supply factors, they can use technology to manage the available resources optimally. The emerging field of decision intelligence – the application of artificial intelligence for making better decisions is best suited to provide resource optimization models for companies across different sectors.

Decision intelligence combines data science, managerial science, and behavioral science with artificial intelligence. It visualizes the impact of one decision on several people, processes, and KPIs within an organization. Decision intelligence brings together several possibilities and solutions to determine the best way to get the desired results from a technology perspective. Ranging from what customers to target for an ad campaign to the most optimal supply chain routes, decision intelligence can help organizations save time, resources and increase profits.

For instance, in the non-profit sector, organizations dealing with starved resources can bank on decision intelligence for optimal solutions. Nagarro is currently working with an international NGO in North America. The non-profit was facing issues in the allocation of ambulances due to high patient count, and low availability of ambulances. Our team developed a decision intelligence model that would allow the best use of the resources. The solution will optimize the response time to reach and attend patients based on the criticality of different patients, the location of the ambulances, and the time taken to get the hospitals in different scenarios.

We started by collecting historical data on demand, both long term and short, demographics of the region, temporal data for incidents, location coordinates for incident locations and ambulance stations, availability of paramedical staff, among other things. The historical data was segregated on a regional basis, predicting demand by different ambulance types and demand in case of events such as a game or concert. Once the data was collected and sorted, predictive analysis was done to forecast the daily / weekly prediction of ambulance demand, using historical demand patterns.

The data entered into an AI model created a decision support tool. In a nutshell, we developed a demand forecasting model using a machine learning algorithm. It was supported by an optimization solution for the ambulance locations to reduce the response times for the patients. The decision intelligence model led to ~10% improvement in the utilization of the ambulances, and the NGO covered 150 more patient calls over one month.

Non-profit and healthcare organizations might have been the ones worst impacted by the pandemic, but the shortages of resources have affected all the sectors. Decision intelligence is a robust technological aid that can help optimize resources across different sectors. For instance, companies use decision intelligence to ascertain the optimum amount of inventory required and the most optimal time to order it in the retail industry. One could also apply decision intelligence to network optimization and to improve sustainability.

The use of AI isn’t limited to the optimization of inventory. Any marketing-driven business, including retail companies, can employ AI to decide on investments in different marketing channels such as online and television advertisements. While companies could also analyze past data with data analytics, decision intelligence allows them to assess the consequences of a particular decision. For instance, a decision intelligence model can help a retail company estimate its sales if it chooses a specific assortment of products for a particular store compared to another store. It can also help identify the required number of sales personnel basis the past data on footfalls across each store. This helps in better allocation of resources across stores maximize revenue.

The e-commerce sector can employ decision intelligence models for route optimization problems. Finding the minimum distance between two places is simple. But, when we extend this problem to a situation where we need to visit multiple locations (500+) at their preferred times, finding the best route can be complex. Additional complexities can include customer preferences, the type of vehicles available,  vehicles’ capacity, and associated carbon emissions. AI algorithms can solve such problems.

Nagarro recently developed a decision intelligence solution combining heuristics algorithms and AI optimization for a client. We first employ a heuristic algorithm to find a possible sequence of deliveries that satisfies all the constraints. An AI-based algorithm optimizes the series of the customers proposed by the heuristic algorithm. The algorithm minimizes the distance traveled and works under demand and time constraints. We carry out capacity estimation, route plan, and visualization as the following steps of the solution to reduce the total distance traveled and associated carbon emission. In this case, the number of vehicles required decreased from 25 to 18. Similar solutions can be developed for different last-mile delivery space problems.

From logistics to manufacturing, decision intelligence is equally helpful for organizations. In the manufacturing sector, organizations can use decision intelligence to monitor product quality, reduce manufacturing wastage, track energy consumption, and reduce incidents on the shop floor. Predictive maintenance models allow manufacturers to predict if and when equipment will fail and schedule maintenance proactively. This doesn’t just help reduce inefficiency in the production process but also helps improve machine performance. Among all the industries, manufacturing can benefit the most from decision intelligence due to the high involvement of machinery in the manufacturing processes.

“Sixty-five percent of respondents surveyed by Gartner in June 2021 said the decisions they make are more complex than the ones made two years ago. And 53% said they face more pressure to explain or justify their decisions.” The research and advisory firm also named decision intelligence one of the top technology strategy trends for 2022. Decision intelligence is essential for business organizations across sectors. The most significant advantage of the AI-based approach is that its applications need not be restricted to the technical teams. Business managers can also leverage artificial intelligence to make the best decisions with decision intelligence. If your organization wants to add decision intelligence to its technology mix, We can help!

Fill up the form here to get in touch with our experts. 

With inputs from Aanish Singla,  distinguished engineer at Nagarro.