What you need to know:
- Posta should build its capabilities to infuse AI pipelines into their core decision-making across different institutional levels.
- The institution’s operations could also greatly benefit from predictive models to enhance their planning and routing systems accordingly.
Posta’s ill fate can be attributed to low quality of service, poor planning, scheduling and routing, leading to increased missed deliveries and delivery costs, ineffective whole production life cycle and incapacity to perform systemic depth root-cause analysis for these maladies.
The situation has been accentuated by stiff competition from private postal service providers and lower demand for ‘snail mail’, piling pressure on its regional outposts throughout the country, particularly when it comes to handling the “last mile” of delivery.
However, new technology could help to optimise systems for delivering mail. Activities like scanning and routing mail could be automated. That could help offload much of the financial burden on users and boost revenues.
For instance, surveys have revealed that post offices, mostly in Americas, Europe and Asian Pacific have been able to make revenues worth Sh500 billion annually as a result of investing in advanced digital technologies.
The success of the private sector post offices is mainly a result of tapping into such technologies, including artificial intelligence (AI), connected vehicles and lockers, digital warehouses and robotic process automation — automations credited with leading to faster and more reliable delivery services, bridging the gap between current post offices operating with last-century technology and what customers expect in the modern world.
The US Postal Service, for instance, has deployed AI to access points weight and also collect and price mail while post office warehouses in the Netherlands use guided vehicles and robotics to move parcels.
Further, many post offices in Europe are using augmented reality to help with real-time information receivership and revamp operations efficiency.
Posta should build its capabilities to infuse AI pipelines into their core decision-making across different institutional levels. That would allow its leadership to look into daily predictions to see which areas will be most problematic for given addresses (regions) and change operational aspects such as distribution set-up or delivery windows.
They could also inspect the contribution of different factors to predictive performance such as weather conditions or seasonal effects.
The institution’s operations could also greatly benefit from predictive models to enhance their planning and routing systems accordingly.
Those, combined with investments in digital marketing to reach a broader audience through modern sales paradigms, 24-hour chatbots for convenient customer service at a lower price point and online loyalty programmes (a marketing mechanic popular among online retailers and other companies) will help the once-progressive public corporation to rebuild and maintain the sizable customer base that it badly needs for reliable revenue.