Circulr was a start-up that provided a solution for consumer waste by collecting used packaging, washing it, and selling it back to the original brand and product manufacturer so that the packaging could be reused. Instead of building its own washing facility, Circulr rented spare washing capacity from industrial kitchens. The company’s co-founders had ambitious goals for Circulr, but in order to achieve them, there were two essential issues that needed to be resolved. The first issue was that of incentivizing brands, manufacturers, and end-users to reuse their packaging. Disposable packaging remained extremely convenient for consumers, and Circulr needed to develop a collection system that made it easy and rewarding for consumers to place their used packaging in Circulr’s collection bins instead of in the garbage can. The second issue was that of operational scale and configuration. If Circulr were to successfully grow demand and supply over time, how would its operational system evolve to achieve the necessary capacity and capabilities? Could the use of third-party washing facilities continue to be sustainable at scale? How would processes and policies evolve to gain competitiveness?
In November 2018, a bicycle program specialist who worked in the Planning and Sustainability Division at the Washington, DC, District Department of Transportation, wanted to analyze Capital Bikeshare’s bike rental demand for the past two years. Capital Bikeshare was a station-based bike-sharing operator that provided an expansive, multi-jurisdictional transportation system to Washington and the surrounding area. If the bicycle program specialist could determine some significant factors that affected users’ ridership patterns, he could best design his expansion plan of adding 40 new bike-rental stations to the system. He obtained the hourly bike rental demand for October 2016–September 2018 to evaluate how sensitive the demand was to some external factors.
As an e-commerce logistics manager at the national grocery store chain TrixMag, Jim Vector was continually seeking efficiency improvements in the company’s supply chain. Following positive trends in the online grocery segment, Vector was specifically exploring the idea of upgrading parts of TrixMag’s intralogistics warehouse system for more efficient throughput. Well versed in the growing world of e-commerce, Vector knew that TrixMag’s warehouses would soon be experiencing tremendous consumer pressures. Competition was also mounting: if Vector’s segment could not reduce costs, TrixMag would not have the capabilities to maintain the low prices that consumers continually demanded. It had become clear that if Vector did not act soon, TrixMag’s market share would begin to deteriorate.
The manager of Water Operations at the City of London wanted to reduce the cost of pumping water by optimizing energy use. Water Operations had been consistently experiencing higher operational costs, and electricity bills accounted for up to 30 per cent of its direct costs. If the manager could predict the future cost of energy, she could schedule the operation of the water pumps to benefit from periods of low energy prices, potentially saving up to 25 per cent of the energy costs. The manager obtained the hourly Ontario electricity prices from 2003 to 2015, and wanted to use that data to evaluate how accurately she could predict future electricity prices. How should she proceed?