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Case Challenge

THE CURIOUS CASE OF HIGH INVENTORIES AND LOW AVAILABILITY

September 16, 2013

Instructions:

Registered Teams will submit a case analysis/solution document comprising no more than 5 pages of single spaced, 12-point font (including illustrations and excluding TOC, Cover page).

Along with the word document each team must submit a 10-slide presentation of the case analysis/solution suggested.

There is no pre-determined structure to analyse the case. Participants are free to use any format which best illustrates and provides convincing arguments for their idea.

Wherever necessary, the participants must make references to the sources of information and data.

Case presentations will be judged based on the following criteria the originality, creativity and uniqueness of the idea will receive the highest weightage; the implementability, sustainability and scalability of the idea; its fit with ITCs vision and the manner in which it can leverage ITCs strengths; the thoroughness of research, analytics and economic logic used to defend viability and execution of the idea.

Last date for submission of case solutions is 25th September 2013. Teams must send their entries to the email ID provided for the campus.

For full details please refer to the Interrobang Season 3 Case Challenge Brochure available with your Campus Point of Contact or contact [email protected]. The e-Brochure is also available at our Facebook page itchubnscope.

ITC Interrobang Season 3 Case Challenge: Curious Case of High Inventories and Low Availability

THE CURIOUS CASE OF HIGH INVENTORIES AND LOW AVAILABILITY

ITC Interrobang Case Challenge 20131

Personal Care Products Business:

Since its inception, ITCs Personal Care Products Business (PCPB) has been continuously venturing into new categories with an ambitious plan to be the market leader in emerging opportunities. The business has the advantage of an established physical distribution network with an unparalleled reach into the hinterlands of the country. PCPB started its journey with established categories like soaps and shampoos where there is a high degree of predictability. However, as it enters into the unchartered and premium territories with >30% margins, the supply chain team started facing several teething issues. The team was stuck with high inventories and low fill rates. Responsiveness to react to changes in consumer demand preferences and moves by competition became a limiting factor to the competitiveness of business. There have been several heated discussions in meeting rooms. Consultant from XYZ, Mr Sundaram was appointed to spearhead the team with an objective of finding feasible & sustainable solutions to the problems haunting the Supply Chain Team. Meeting Room: ITC Centre:

We are losing on sales due to abysmal availability of stock in the market, pointed a visibly upset Mr Sarang, Head of Sales. With fill rates as low as these, competitors are getting away with a chunk of market. What a new entrant loses is not one unit but an opportunity to have a potential relationship with consumers, an opportunity which we may not get again. Sure fill rates have been lower, but look at the accuracy and fidelity of the estimates. How do we provide service when our forecasts are so unreliable, the supply manager asked the demand planner. Chart: Fill rates of premium portfolio:

Table: MAPE*:

*MAPE stands for Mean Absolute Percentage Error defined as MAPE = |Forecast-Actual|/Actual x 100

1This Case is developed by and is the sole property of ITC Limited. This is for academic purposes only and is not intended to be copied or displayed or reproduced at any place outside the Campus.


Table: Bias

Forecast bias = (Forecast-Actual)/Actual x 100 Products are very seasonal in nature and we dont have enough historical data to forecast. Take for example, a SPF lotion sells well in summer but has reduced sales in winter. Actual sales data is further skewed due to lost sales on account of no stock. For a product with 5 months sale period, it is difficult to predict Chart: Primary and secondary sales over 10 periods

The finance manager looked conspicuously worried. While everyone is crying no stock, I am sitting with a huge value which will be written-off for expiry and several tons of stock is transitioning from slow moving to non-moving. Chart: Inventory ageing chart (Factory + WSP)

(These categories have a >50% reach to consumers via modern trade that give no forecasts (shop in shop and mall formats). Organised players have stringent requirements of >75% freshness limiting system ability to keep inventories.)


Ajay Srivastava, brand manager chips in. I want to offer better value to consumers by providing products with natural extracts which will increase our sales. But the aggregate pipeline is so high that I have to wait for 3 months before the new product reaches the consumer. Chart: Current inventory position (days of cover)

Current Network Design

The Distribution Network is spread across 1500+ WDs and 55+ WSPs. There are approximately 15 logical Modern Trade WSPs besides these. Modern trade WSP is serviced by WSPs which are located regionally. There are 2 factories- at Haridwar and Chandigarh where premium SKUs can be manufactured. There is a hub in north (Roorkee) and one in south (near Warangal). Figure: Network Map


Existing network flow model is fairly linear in nature. ITC manages inventory till wholesale distributors.

Shipment logic:

From Factory to hub/WSP, weekly STRs are used to generate the requirements. STR = Target inventory norm Stock on hand Stock in transit. The same logic is used to generate delivery requirement (ideal delivery order) at WD Norms vs. actual:

Norms are defined for each SKU and location combination. Norm for a sample SKU of Category I is as below (days of cover)

Norms Factory Hub WSP WD

Cat I 20 4.4 14.9 10.0

Manufacturing cycle:

Products have monthly plan and manufacturing cycle. Manufacturing products < 300 kgs results in 40% loss of material and more importantly results in potential stock-out of input materials in next run. Shipment of finished goods:

Lead time is different for every location (refer annexure). CS corresponds to time between two truck load connectivity at WSP. Problem statement

If you were in place of Mr Sundaram, how what recommendations would you have for business to improve the supply chain.

What levers would you use to improve the service levels?

How, according to you, should ITC service the modern trade orders?

What should be ITCs shipment and inventory strategy at various echelons of supply chain?

How, according to you, should ITC reduce response time to market?

What are the recommended service levels at various stages?


Annexure-I Table: Transit Times from Source to Destination.

Location Roorkee Warangal Chandigarh Haridwar

Ahmedabad 3.6 4.8 4.8 4.8 Aurangabad 4.8 2.4 7.0 6.0

Bangalore 9.6 2.4 9.0 8.4

Belgaum 7.2 2.4 6.0 7.2

Bhopal 3.6 3.6 4.8 3.6

Bhubaneshwar 7.2 4.8 8.4 7.2

Calcutta 7.2 6.0 7.2 6.0

Calicut 13.2 3.6 11.0 9.6

Chandigarh 1.2 6.0 1.2 2.4

Chennai 9.6 2.4 10.0 8.4

Delhi 1.2 6.0 1.2 1.2

Ernakulam 10.8 3.6 11 10.8

Ghaziabad 1.2 6.0 2.4 1.2

Guwahati 14.4 8.4 14 12

Haridwar 1.2 6.0 3.0 1.2

Hyderabad 9.6 1.2 7.2 6.0

Jabalpur 4.8 3.6 6.0 4.8

Jaipur 1.2 6.0 2.4 2.4

Jammu 2.4 7.2 2.4 2.4

Jamshedpur 7.2 6.0 7.2 6.0

Jodhpur 2.4 6.0 3.6 2.4

Kanpur 2.4 6.0 3.6 3.6

Karnataka 9.6 2.4 9.0 8.4

Kundli 1.2 6.0 2.4 1.2

Ludhiana 1.2 7.2 1.2 1.2

Mumbai 4.8 3.6 7.2 6.0

Nagpur 4.8 2.4 6.0 4.8

Parwanoo 1.2 6.0 1.2 1.2

Patna 6.0 6.0 6.0 4.8

Pune 6.0 2.4 7.2 6.0

Raipur 8.4 6.0 7.0 6.0

Saharanpur 1.2 6.0 1.2 1.2

Sambalpur 4.8 4.8 7.2 6.0

Siliguri 8.4 10.0 10.0 9.6

Srinagar 6.0 14.0 4.8 3.6

Tirupati 10.8 2.4 10.0 9.6

Trichy 10.8 3.6 9.0 8.4

Varanasi 3.6 4.8 4.8 3.6

Vijaywada 9.6 1.2 8.0 7.2

Vizag 9.6 2.4 8.0 7.2


Table: Cycle of replenishment Location CS

Ahmedabad 4

Aurangabad 10

Bangalore 10

Belgaum 10

Bhopal 12

Bhubaneshwar 6

Calcutta 18

Calicut 7

Chandigarh 10

Chennai 4

Delhi 7

Ernakulam 10

Ghaziabad 10

Guwahati 7

Haridwar 4

Hyderabad 6

Jabalpur 10

Jaipur 5

Jammu 4

Jamshedpur 10

Jodhpur 10

Kanpur 18

Karnataka 10

Kundli 10

Ludhiana 4

Mumbai 4

Nagpur 16

Parwanoo 10

Patna 10

Pune 5

Raipur 11

Saharanpur 6

Sambalpur 6

Siliguri 18

Sri Nagar 14

Tirupati 20

Trichy 7

Varanasi 17

Vijaywada 17

Vizag 18

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