Chapter 6

Routine market analysis and reporting

6.1 Introduction

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.

First, a 

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

delays.

Second, the 

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

 (error checking

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.

Finally, the

 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

failure).

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