Improving Monthly Demand Review Meeting Effectiveness for Desklib

This presentation by Desklib provides an action plan for improving the effectiveness of monthly demand review meetings. It includes descriptive analytics, a balance between country and product level, segmentation/prioritization, performance indicators and relevant models, and an improvement plan with quarterly analytics. The presentation emphasizes the importance of analyzing average sales, prioritizing products, and developing accurate sales forecasts.

Action Plan for Forecast
effectiveness Improvement
Monthly Demand Review Meeting May 2018

Descriptive Analytics
Jan-18
Mar-18
May-18
Jul-18
Sep-18
Nov-18
Jan-19
Mar-19
May-19
Jul-19
Sep-19
Nov-19
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A graph of Average Sales Forecast against the
calendar year/Month
APR 2017 Forecasting cycle
MAR 2017 Forecasting cycle
FEB 2017 Forecasting cycle
JAN 2017 Forecasting cycle
Calender Year/Month
Average Sales
Forecast

Descriptive Analytics
 A comparison of the average sales forecast
indicate that there is a steady increase in
sales from January through to January
 We expect the same trend in the following
year,2019

Balance Between Country and Product Level
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
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KARATE 025 EC 12x1 L
IMIDACLOPRID 20 SL 12x500 ML
CURACRON 500 EC 12x1 L
ACTARA 25 WG 10x10x24 G

Segmentation/Prioritization
 There is no significant different in average
sale volume across the products
 Therefore, there should be equal supply to the
market
 However, in case of a priority then Karate 0.25
BC 12xL should be considered
 This product should be considered since it has
the highest average sales volume.

Performance Indicator and Relevant Model
 The best way to check for the performance is by evaluating
the average sales.
 Average can be forecasted accurately.
 We can develop a model for accurately predicting the sales.
 Given the actual sales and the forecasted sales for 2017, the
following relationship has been develop:
 Forecasted sales= 0.9033*(Actual Sales)+ 507.79
 This implies that if we have the past sales records, we can
use this equation to predict the future sales accurately

Improvement Plan and Quarterly
Analytics
 An effective way of improving sales forecast is
by making monthly forecast based on average
sales
 Apart from monitoring average ales, there
should be analysis based on any variation on
actual sales
 Another important analysis should be based on
hypothesis testing of whether there is any
significant difference in average sales across the
months