Routine market analysis and reporting
Although reporting is the final step in the process, it is important that the reporting of price
analysis be accurate, timely, and accessible to your users. Good analysis can only be useful
if it is well written and well presented. Reporting is the final activity in a process that
involves winnowing lots of data (sometimes sending conflicting signals) and turning it into
information that is actionable by decision makers. It is this distillation process that
determines the effectiveness of the reporting. This chapter provides suggestions on routine
analysis and reporting of market information.
6.2 Routine market analysis
6.2.1 Data processing activities
The regular and rapid processing of price data is very important in generating useful and
timely early warning information. There are four steps that need to be done to efficiently
process the price data.
data processing plan
needs to be developed. In this plan all aspects of the
process from collection to archiving of the data need to be specified. Also, there
should be a handbook (brief) that documents all of the procedures relating to the
processing of the data. This helps lessen the impact of staff turnover that we have
observed in many national early warning units. This plan should clearly state the
responsibilities of staff members within the early warning unit to avoid confusion and
collection of data from the relevant institutions
(e.g., the Agricultural
Marketing Information Centre) should be done immediately after the data are available.
It is important to obtain their data processing schedule. Timely reporting begins with
timely collection of price data.
Third, there should be a systematic procedure to
input and review the data
and quality control). Although these data are collected from reliable organizations,
everyone makes mistakes. These data should be added to the current price database and
some key market commodity clusters reviewed.
data should be archived
for future use as a back up in the unlikely situation that
they get damaged or lost. Although it is rare, there have been some circumstances that data
at the organization that has collected the data have lost all of their data (e.g., due to computer