Production Capacity Analysis


Cycle time analysis was used by the World Bank's Foreign Investment Advisory Service (FIAS) to look at constraints in the Ugandan coffee sector. The Ugandan government implemented a decentralization process that increased the number of bureaucratic procedures individual districts imposed and led to the implementation of levies on investments and shipments in and between the districts. A cycle time analysis showed that it took 20 days for a container of coffee to pass from Ugandan growers to the ports in Mombassa. The detailed analysis revealed that it only took 2 days to transport the container but on average 18 days were added through delays at multiple interception points across the country. When compared to better performing coffee industries in Colombia and Costa Rica, where containers reached the port in seven days and one day, respectively, it became clear that local regulation was having a negative impact on Ugandan producers’ efficiency and competitiveness. Thus, streamlining the procedures became a focus of government and industry leaders. In addition to sub-national regulations and customs, other constraints such as infrastructure limitations at ports and airports, informal logistic systems and inefficient manufacturing processes can add an enormous amount of time to the cycle.


A throughput analysis conducted for the Indian sugar sector (see graph right) showed that if national government regulations are passed, requiring the blending of ethanol into petrol at 10 percent by volume, the demand for ethanol will reach almost four million tons by 2017. Currently, the sugar mills have a throughput of 3 million tons of ethanol so by 2017, there will be a shortfall of almost a million tons. This analysis is very useful for state governments in India who have a strong sugar sector and want to promote investment in sugar mills. This type of analysis helps focus stakeholders on upgrading initiatives and shows possible investment opportunities.

Throughput analysis can also be applied to service sectors and does not need to be inventory focused. The USAID Global Workforce in Transition (GWIT) project conducted an assessment of the ICT workforce in Sri Lanka which showed a constraint within the education sector. The ICT industry was growing so quickly that schools training future employees could not keep pace with demand. GWIT surveyed ICT firms and found that the industry had a total demand of 4,300 graduates in 2005 and in 2006 but could only fill 3,600 jobs in each year. This left a shortfall of about 1,400 graduates. GWIT drafted a workforce strategy encouraging technical schools to provide ICT boot-camp training to help fill the gap.

Throughput can also be measured by inventory turns, which measures the average amount of inventory on hand that is sold in a year. This analysis is important to enterprises and the value chain as a whole because it shows how much working capital is locked up in inventory, which might otherwise be used for investments in upgrading. To find how much inventory is turned in a year, annual sales are divided by the average inventory on hand. The USAID-funded Pakistan Initiative for Strategic Development and Competitiveness (PISDAC) project used this analysis for the furniture value chain. One recommendation of the resulting strategy was for small furniture manufacturers to upgrade their processes by investing in solar kilns to dry their wood. The manufacturers traditionally used “seasoning” of wood which could keep wood in inventory for one to three years in order for it to dry; manufacturers then turned their inventory over only one time or less per year, locking up working capital for extended periods of time. By upgrading the drying process using solar kilns, these manufacturers could turn their inventory over almost 20 times faster, thus reducing their working capital requirements. Analysis showed that the investment to upgrade would be a wise decision and thus the project, working with the private sector, invested into five pilot solar kilns.

Suggestions for Collecting Production Capacity Data

  • When collecting information on cycle time, it is often easiest to interview managers from the lead firms in the country, who often have an understanding of the length of time that products take at each step of the chain. Sometimes more detailed information gathering is needed - asking each player in the value chain their average cycle time and what type of variance can be expected.
  • The easiest and cheapest way to collect data for a throughput analysis is to identify the main bottlenecks in the value chain by locating where large build-ups of inventory often occur. By analyzing the throughput at these bottlenecks, the throughput of the entire value chain can be inferred.
  • Information can best be collected for inventory turns by implementing a small survey or interviewing representatives from each part of the value chain. Surveying high, average and low inventory levels and prices will generally give the analyst reliable estimates.