Optimizing trips schedule and routes can aid field-service organizations and delivery business in devising an efficient schedule for trips ahead of time and plan out the best set of routes for their field personnel and drivers each day and over an extended time horizon. Through optimization, these organizations are better equipped to provide services in a timely manner, cover multiple destinations in the most efficient way possible, and improve customer satisfaction. Less time spent in driving ultimately leads to substantial savings on fuel costs, more time onsite and more in-between stops to be covered along the way. With a large geography of hundreds and thousands of target sites, manual-based means of figuring out the best schedule and routes will undoubtedly result in poor planning, waste of resources and loss of productivity. With more entities grappling with the challenging task of containing cost and optimizing resources particularly in the face of rising fuel prices and labor wages, a departure from traditional approaches and adoption of AI-powered and data-driven techniques will undeniably provide substantial benefits back. It has the potential to remove the guesswork out of planning and set operation mode in autopilot.
Abu Dhabi Agriculture & Food Safety Authority (ADAFSA) is the local authority in charge of agriculture, food safety, food security and biosecurity in the Emirate of Abu Dhabi of the United Arab Emirates. With around 150 inspectors that conduct routine site visits for more than 15,000 different establishments such as restaurants, slaughterhouses, greenhouse facilities and others, ADAFSA maintains a fixed inspection schedule assigning target locations to inspectors based on proximity approximation, ad-hoc examination, and conventional wisdom. The statistics and analytics division of ADAFSA has long recognized the role of AI and machine learning in transforming the core inspection business of ADAFSA. With a-priori knowledge provided about the inspectors’ initial location, windows of working hours along with sites to visit ranked at 3 different levels of priorities, ADAFSA leveraged ZIGGY, Cognitro route optimization solution, to optimize the inspection schedule route. ZIGGY scours the entire inspection temporal horizon and seeks to maximize sites coverage with minimal total distance travelled in favor of meeting priority constraints.
To assess the efficacy of the model, we developed a benchmark analysis of the model impact on operations for 100 inspector and 3000 sites, across areas of cost saving, improved productivity, and enhanced efficiency; and the results came to substantiate our claim. Overall, the benchmark revealed a significant ROI of 32%-36% gain manifested through different areas. First, saving on cost associated with the vehicle’s usage including rental and fuel were amongst the most intuitive and tangible sources of benefits, creating an annual cost saving of about 0.6 to 1M AED with about 80% of the cost coming from vehicles usage and rentals. Another indirect but substantial source of benefit came from the productivity gain reflected in an annual cost avoidance of unnecessary labor of about 13M AED in salaries. That brings the total cost saving to about 14M AED annually.
“ZIGGY helped us transform our inspection process resulting in a significantly improved efficiency and enhanced inspectors’ productivity, saving us therefore from incurring substantial unnecessary cost”
Aisha Al-Shamsi, Chief Data Officer