Complexity study for the beverage industry (summary)

Delft University of Technology

Faculty Mechanical, Maritime and Materials Engineering Transport Technology

R.K. Geurts Complexity study for the beverage industry

Masters thesis, Report 2005.TL.6991, Transport Engineering and Logistics.

As a result of strong competition between brands in the beverage industry the growth for Unilever's Lipton Ice Tea has stagnated and the profitability is decreasing. As a reaction the Marketing and Sales Units (MSU) in the different countries in Western Europe try to maximize their expansion by launching new products and offering promotional sales.

Due to these new products the number of products in the product portfolio of Lipton Ice Tea has expanded and the complexity of the product portfolio has increased.

To fully understand the consequences of this increase in products, a study with regard to the current situation of the product portfolio (the complexity) has been performed.

In this study the influences of the number of products on the production costs and opportunities of adjustments of the product portfolio are examined. The complexity study has been done for Lipton Ice Tea at European Supply Management Foods (ESM), the European purchasing organization of Unilever. Scope of the study are the countries: Belgium, France, Germany, Italy, the Netherlands, Portugal, United Kingdom and Switzerland. Lipton Ice Tea is a tea-based beverage available in a number of different formats and two variants: sparkling (carbonated) and still (non-carbonated). Besides the regular variant, Lipton Ice Tea is available in a large variety of flavours.

Lipton Ice Tea is produced at third-party copackers, who have the equipment to produce (soft)drinks. As is common in the beverage industry the basis for Lipton Ice Tea is a kit, produced by Lipton Ice Tea, that contains a secret composition of raw materials (like tea powder and flavours juices). The remainders of the ingredients are added by the copacker.

The manufacturing and distribution of Lipton Ice Tea is done in a co-ordinated teamwork between copackers, Material Group Managers, Marketing and Sales Units and Product Technical Group planners.

Analysis

The total Ice Tea market for Western Europe in 2004 was 2256.3 billion litres. Of this total market Lipton Ice Tea had a 24% market share. Lipton Ice Tea's small market shares in two countries with the biggest markets (Germany and Italy) caused this relatively low market share for Western Europe. When the ten formats of Lipton Ice Tea are compared with their net product sales, gross margins and volumes, two types of formats can be defined. The first group are the tactical formats, which have small volumes, but high gross margins. The second group are the volume driven formats (can and PET), with lower gross margin but large volumes.

These two markets make a good combination. The volume driven market realizes a high profit because of the large produced volumes and forms a rigid basis for the rest of the formats. The tactical markets realizes a high profit with higher margins and their more customer driven approach binds customers to Lipton Ice Tea.

For a more detailed analysis the Lipton Ice Tea products are separated to the level of Stock Keeping Units (SKUs). For the analysis the itemised SKUs and their generated net product sales (NPS) are shown in two stacked columns in figure 1 The left column shows the generated amount of NPS and the right column shows the percentage of SKUs in each group. The numbers in the right column are the number of SKUs in the corresponding group.

Figure 1; SKU analysis Lipton Ice tea Europe 2004

For the eight Marketing and Sales Units in Europe the product portfolio for 2004 included in total 311 SKUs. Only 30% of these SKUs generate 80% of the net product sales while the last 45% of the SKUs just add 5% to the net product sales.

From the analysis of the generated net product sales of the SKUs a more detailed study with regard to the SKUs that together generates the last 5% of the net product sales has been performed.

In this study the gross margins for the different formats of Lipton Ice Tea are plotted against their net product sales (x1000 Euro). The gross margins are given in comparison with a reference value. The surface of the bubbles corresponds with the total produced volume in litre (x1000) Lipton Ice Tea for 2004 and the numbers behind the formats are the numbers of SKUs in the formats [see figure 2].

Figure 2; SKUs Lipton Ice Tea generating last 5% net product sales (2004) From the study it is clear that over 75% of the formats in the tail are PET bottles or cans.

For Lipton Ice Tea the largest costs are the bought-in costs. In figure 3 a more detailed overview of the bought-in costs is given. The packaging costs and raw material costs contain several costs. The conversion costs only contain the costs for the production at the copackers and are the major part of the total bought-in costs.

Figure 3; bought-in costs breakdown for Lipton Ice Tea (2003)

Because of the high percentage of PET bottles and cans in the tail [see figure 2] the bought-in cost breakdown for these formats are studied in more detail. From this analysis follows that for the PET bottles have the highest conversion costs. The conversion costs are negotiated with the copackers and partly depend on the composition of the product portfolio.

Because the conversion costs are the biggest part of the total bought-in costs a study with regard to the influence of the composition (complexity) of the product portfolio on the production costs (so called conversion costs) is performed. From the literature no useful information or models are available. That is why with information from one of Lipton Ice Tea's copackers (Emig, Calvörde) and Unilever's Market Intelligence a cost model is built.

Cost model

With the cost model and the final throughput of the production line the cost price per litre Lipton Ice Tea can be estimated. This throughput depends on the maximum technical capacity and the Overall Equipment Effectiveness (OEE) of the production line. The OEE measures the performance of a production line at a factory.

The technical capacity is known, but the OEE can vary because of the changeovers needed to set the production line for different products (SKUs). The number of changeovers depends on the complexity of the product portfolio and so does the Overall Equipment Effectiveness.

With the use of two OEE models used within Unilever, a specialized OEE model for the production line at Emig is generated.

To measure the influences of changeovers the downtime losses caused by changeovers are added at the end of the model and the model is divided in two parts (Time part and Production part).

After verification with the current situation the Overall Equipment Effectiveness is defined as:

The Time OEE is constant (62.4%) and is determined by the working hours at Emig. From the verification with the current situation the Production OEE is divided in two parts:

A Performance and Quality Equipment Effectiveness (P&Q EE) that handles the errors and efficiency of the operating production line; and a Changeover Equipment Bought-in costs breakdown Effectiveness (Ch EE) that handles the effects of the time needed for changeovers on the available production. While Emig can not exactly quantify the Performance & Quality Equipment Effectiveness it is estimated with verification with the Production OEE at Emig. The result is an Overall Equipment Effectiveness at Emig of 32.5% [see table 1].

Table 1; total OEE Emig (2004) Total OEE

Time OEE 62.4 %

Production OEE

Performance & Quality EE 55.0 % Changeover EE 94.8 %

Total OEE 32.5 %

From the verification with the Production OEE at Emig follows that the efficiency losses and the errors of the production line after changeovers have more influences on the total OEE than the time needed for changeovers [see table 1].

The defined OEE is used with the cost model to investigate the influences of the number of products on the production costs for a litre Lipton Ice Tea. The cost model is made with data from Emig and general information from Unilever's Market Intelligence.

Input of the cost model is the total Operating Equipment Effectiveness to calculate the throughput of the production line. Output of the cost model is the cost price in Euro per litre Lipton Ice Tea at Emig.

Settings of the cost model are general costs that can be specified in: raw material costs, costs for utilities, operating costs, overhead expenses and financing charges. With the settings filled in a cost price estimation per litre Lipton Ice Tea at Emig for 2004 is made, this average cost price is 0.24 Euro per litre. The cost price of the cost model is verified with the cost price per litre at Emig. For the cost price the total expenses at Emig for 2004 are divided by the total produced volume Lipton Ice Tea in litres.

The cost price at Emig is 0.29 Euro per litre, with conversion costs (copacking fee) and 0.21 Euro per litre, without this copacking fee [see figure 4].

Figure 4; cost price built up

The copacking fee per volume bottle (0.5 litre or 1.5 litre) is always the same and includes the general costs for the production (like operating costs, overhead expenses and financing charges) and the profit for the copacker.

The cost price from the cost model is in between the cost prices for the production at Emig with and without copacking fee. The gross margin of Emig is not known, but should be the difference between the actual cost price with copacking fee and the cost price from the model. This difference is

0.29 - 0.24 = 0.05 Euro and results in a gross margin of 17%, which is reasonable.

Based on the comparison with the actual cost prices, the cost model is assumed to give a reasonable estimate and that the cost model can be used to compare the cost price per litre for different product portfolios.

The different product portfolios follow from the number of products (SKUs) within the product portfolios. The number of products influences the needed number of changeovers and production runs and thereby influences the Overall Equipment Effectiveness.

The Overall Equipment Effectiveness is the input of the cost model and is given in formula 1. For the estimation of the cost price with the cost model first the Overall Equipment Effectiveness at Emig is estimated.

For the Overall Equipment Effectiveness the Time OEE is constant (62.4%). The Changeover Equipment Effectiveness follows from the number of changeovers and is related to the number of products and production runs.

With a utilization of the production line of 50% for Lipton Ice Tea, there are 2725 hours of production in 25 weeks. With two obligatory cleanings per week this results in a minimum of 50 production runs.

This means 50 changeovers are combined with the time needed for the obligatory cleanings, the rest of the changeovers must be done during available production time.

The Changeover Equipment Effectiveness is calculated with formula 2 in which the effective time is the time available for production (2725 hours) and 'N' the number of production runs.

At last the Performance and Quality Equipment Effectiveness is estimated. Because the influences of the number of changeovers and production runs on the Performance and Quality Equipment Effectiveness are not exactly known at Emig a model is made to estimate the influences.

The model gives a relationship between the number of production runs and the Performance and Equipment Effectiveness and is based on presumed efficiency losses that occur after every start-up of the production line.

For the first five hours after every start-up the Performance and Quality Equipment Effectiveness as listed in table 2 is assumed. After these first five hours a P&Q EE of 60% (maximum) is assumed.

Table 2; assumed behaviour Performance and Quality Equipment Effectiveness Performance & Quality Equipment Effectiveness behaviour

Hour 1 2 3 4 5

From verification with the actual production data at Emig for 2004 follows the assumed efficiencies in table are reasonable and the corresponding formula is derived.

In formula 3 'N' represents the number of production runs and 'CT' the changeover time. With the Changeover EE and the assumed P&Q EE the total OEE from formula 1 results:

with 'N' representing the number of production runs and 'CT' representing the changeover time.

For the estimation of the influences of the number of production runs on the cost price per litre an average changeover time of 1.4 hours is used in formula 1. The Overall Equipment Effectiveness from formula 1 is used as input for the cost model. For a number of production runs (N) the corresponding cost prices are estimated.

For a clear view of the influences the cost price per litre is estimated without the raw material cost per litre (because these costs are not influenced by the throughput). The cost prices, without raw material costs, for different number of production runs are plotted in figure 5.

Figure 5; cost price per litre Lipton Ice Tea with average changeovers Adjustments of the product portfolio

The cost prices per litre from figure 5 are used to compare the costs of four different product portfolios with the cost of the product portfolio at Emig with 30 SKUs and 139 production runs. With the comparison the influence of the number of production runs on the total costs for the product portfolio can be examined.

For the comparison the raw material costs are added to get the total cost price per litre per production run and a total produced volume of 50 million litres is assumed.

The four examined product portfolios follow from the minimum number of production runs, two adjustments of the number of SKUs in the product portfolios and an assumed high number of production runs.

The minimum number of production runs in 25 weeks is 50. Deleting two kinds of secondary packaging at Emig results in 18 SKUs, with an average of 5 production runs per SKU the total number of production runs becomes 90.

Adding one flavour for two countries in four secondary packaging results in 8 extra SKUs and 40 extra production runs. With 139 production runs for the actual product portfolio this results in 179 production runs.

To examine the influence of even more production runs a number of 225 production runs is assumed. The differences in the production costs for the four adjusted product portfolios are given in figure 6.

Figure 6; savings and extra costs for adjusted product portfolios compared with the total production costs for a product portfolio with 139 production runs

Figure 6 shows that the costs for deleting or adding a number of SKUs at a copacker are substantial. Especially when it is assumed that the total costs for raw materials (approximately 80% of the cost price) are fixed and hard to reduce. For Emig a product portfolio with 90 production runs results in a saving of 4.3% on the 2.7 million Euro (20% of the expenses at Emig) that European Supply Management can influence with the composition of the product portfolio.

It is presumed the saving even would be higher, because the changes in the number of SKUs are assumed to have a bigger impact on the cost price than estimated. A second reason is that the effects of a smaller product portfolio on the organization needed to manage the product portfolio are not included in this analysis.

Besides the effects of adjustments of the product portfolio on the production cost the effects on the generated net product sales and gross profit for the whole product portfolio are examined in a separate study.

For the adjusted product portfolios a number of SKUs are deleted using figure 1. The influences of the number of SKUs on the cost prices and the 'back office effects' are not included in this study.

The examined product portfolio is the total product portfolio with 311 SKUs for Western Europe for 2004. It is assumed 10% of the volume of the deleted SKUs is added to the volume of the remaining SKUs. The 70 SKUs with the lowest net product sales are deleted from the product portfolio. Then the changes to the net product sales and the gross profit for deleting 139 SKUs are examined. Finally a product portfolio, for which the 221 SKUs with the lowest net product sales have been deleted, is examined. In table 3 the product portfolio for 2004 and the three assumed adjusted product portfolios are given.

Table 3; adjusted product portfolios

Volume (L) NPS (C) Gross Profit (C) Product portfolio 2004 475,114,119 332,326,398 133,782,762 New 241 SKUs+10% portfolio 469,480,868 329,888,920 133,783,927 New 172 SKUs+10% portfolio 453,896,164 318,795,901 130,337,609 New 90 SKUs+10% portfolio 382,997,221 274,334,532 115,756,702

Deleting the last 70 SKUs results in a gross profit that is a bit higher than the gross profit for the actual product portfolio for 2004. When almost half of the SKUs are deleted this results in 172 SKUs and only a small decrease of the gross profit.

When 70% of the SKUs are delisted this results in a decrease of less than 14% of the gross profit. Conclusions

From the analysis with the cost model it is concluded that an increasing number of production runs results in an increasing cost price per litre Lipton Ice Tea. The cost drivers for the cost price at the copackers are the numbers of SKUs at the copackers. The numbers of SKUs determine the number and sizes of the needed production runs at the copacker.

For the choice of the SKUs that must be deleted it is important to know what their performance is and what the value added costs of the SKUs are. The remaining SKUs in the product portfolio must be produced in a minimum possible number of production runs, with maximum possible production run lengths.

The resulting composition of the product portfolio can be achieved with the use of 'SMART' complexity: Set up

Achievable Run Times

With this 'SMART' complexity it is possible to offer a complex product portfolio, with a significant number of SKUs, to the consumers for a low cost price. For a more precise relationship between the number of SKUs, production runs and changeovers and the cost price per litre a more detailed study in close co-operation with one of the copackers must be done.

This study must examine the influence of the number of production runs and changeovers on the Performance and Quality Equipment Effectiveness. To decide which of the SKUs must be deleted from the product portfolio a detailed Marketing and Sales study must be done. This study must examine the consumer behaviour of deleting a number of SKUs from the product portfolio, the influence of introducing new SKUs (product cannibalisation) and the costs consumers are willing to pay for (value added costs).

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