FMCG is a highly competitive industry where a company’s
top line may be high and its bottom line can be rather low. Dabur,
one of the largest FMCG players in the country, has consistently
delivered good financial results over the past five years with a
CAGR of 18 percent in net revenue and 33 percent in PAT. Despite
this robust growth, the Dabur management believed there is
potential to derive incremental growth through supply chain
efficiencies.
However, it became a challenge for the management to further
increase the company’s efficiency to improve its
profitability and increase its bottom line.
Supply Chain Exercise
IT has always been an integral part of Dabur. With the help of its
IT team, the management captured the total opportunity potential
from a supply chain exercise across different levers.
The findings of this exercise follow:
- It was observed that incremental revenue through lost sales
accounted
for six percent revenue.
- Lost revenue is often the result of a shortage in stock.
- The company found that cost reduction was another area in
which
they could become more profitable.
- Damaged goods formed about 10 percent of the existing
spend.
The company thus estimated that this exercise would result in
benefits of about ` 50 to 75 crore.
Dabur’s supply chain is far more complex than other FMCG
firms in India
given its large product portfolio. This made the supply chain
exercise fairly
challenging.
“We have a diverse product portfolio with more than 800
SKUs spanning multiple shelf life: Food, Personal Care, Home and
Healthcare products. This is a
fragmented and multi-tiered distribution network with more than 10
plants,
over 40 warehouses and about 1,500 distributors. We also have a
large fragmented front-end and seasonal products,” informs
Anil Garg, GM – IT, Dabur.
Forecasting is critical to any FMCG company to meet demands,
prevent
overproduction, underproduction etc.
It was hence imperative for Dabur to improve its forecasting in
order to
grow further.
Inefficient forecasting
At Dabur, forecasting is done at various levels. Sales forecasting
is done with
the help of market research data collected from the field.
Based on the
sales forecast, demand and distribution planning is done. This
includes a product
requirements plan and a confirmed delivery schedule.
However, since most of the work was done manually, this process
resulted in
certain issues. For instance, the supply chain planning was driven
by top-down
forecasts at the brand level—subject to large variations.
Hence, there was
low forecasting accuracy even for the firm forecasts. Moreover,
there was an
absence of visibility into customer stock and secondary sales
details.
When it came to demand and distribution planning, there were no
formal inventory norms based on demand and supply variability.
Time-phasing of requirements was driven by supply rather than
demand considerations. Further, manual Excel-based planning
resulted in poor responsiveness of the planning cell.
As for supply planning, there were no formal prioritization
rules for production scheduling. There were also delays in running
the Master Production Schedule (MPS) and Materials Requirement
Planning (MRP) due to multiple Rolling Production Plans (RPP) and
manual intervention.
Capacity constraints were not evaluated across multiple RPPs and
there was no performance metrics dashboard.
Finally, there were issues even in production planning.
Intermediate planning was not a formal step in the planning cycle.
There were also no formal Receivables Management (RM) and Payables
Management (PM) inventory norms. Moreover, there was loose
integration of procurement planning with production planning.
Says Garg, “This entire process was fraught with
underutilization of information. This resulted in significant costs
across multiple value levers.” Low forecasting led to excess
inventory, high operational costs and lost sales.
 |
"The entire sales volume plan is generated by the system
once you input the growth target. With Excel sheets, human errors
were high ”
- Anil Garg, GM - IT, Dabur
|