Financial performance, products and local market

Most pricing decisions are made at each profit center or plant. As will be shown later in this section, pricing is not a well defined area of prtice in SCAP and therefore not a well defined process where pricing ac-tivities can be clearly separated from other acac-tivities more generally re-lated to sales or operations. Hence, the pricing process is embedded in the overall sales process and contains activities closely related to other functional areas within the unit. At the level of individual profit cen-ters there are three different types of pricing taking place.

1. Everyday pricing of new but non-strategic accounts – ordinary day-to-day pricing of new accounts that is routinely managed by responsible officials.

2. Everyday pricing of current accounts with established relationships – renegotiation of established contracts or prices is managed by responsible officials.

3. Strategic pricing (tenders, large key accounts, etc.) – novel and non-routine situations which often involve several members of the management team.

On a general level, the process leading up to the pricing decision and the closing of a deal with a new customer can be described as a se-quence of activities.

1. Customer assessment – Sales opportunities are identified, discus-sions with customers are initiated, and customer needs are specified in terms of a specification or inquiry.

2. Preliminary pricing decision – Mechanism and responsibility de-pend on the local approach.

3. Negotiation – Negotiation of final terms of the agreement.

6.1.3 Financial performance, products and local market

Even though the variation in average square meter price and operating margin can function as an indication of the extent units have succeeded in pricing, there are important restrictions on the comparability of these measures related to differences in product portfolio and local industry characteristics.³⁸ Having said that, there are still some general observa-tions that can be made from comparing the five cases.

All five units are relatively profitable compared to a European average.

Epsilon shows the greatest performance in terms of operating margin followed by Gamma and Delta (see ranking in Table 6.4). Much of the variation in average price can be explained by differences in product portfolio. One example of this is Beta’s relatively high ranking on aver-age price compared to their operating margin. Simply put, more value added products made out of more expensive materials that demand more processing naturally give rise to a higher average price without necessarily having the same effect on the sales margin. A potential effect of industry differences can also be viewed when comparing the high ranking of Epsilon on operating margin to the characteristics of the competition in the local market. This shows an extremely high level of industry concentration with the top four suppliers of corrugated pack-aging supplying over 90 % of domestic demand.

As mentioned before, the data presented in Table 6.4 has the character of background information to better understand differences between the five cases. Inferences regarding any causal relationship between fac-tors should be made with caution.

38The financial data is included here only as background information to the differ-ent cases and no claims are made with regard to the correlation between an indi-vidual unit’s financial performance and other observations.

Table 6.4 Financial performance, products and local industry characteristics.

Index³⁹ Alfa Beta Gamma Delta Epsilon

Turnover

2003 100 111 210 212 182

2004 100 127 213 205 173

Change +6 % +21 % +8 % +3 % +1 %

Ranking -04 5 4 1 2 3

Price/sqm

2003 100 218 175 206 167

2004 100 207 170 191 149

Change +7 % +1 % +4 % +-0 % -4 %

Ranking -04 5 1 3 2 4

Operating marg.

2003 133 100 171 135 202

2004 100 104 166 131 210

Change -28 % +7 % +1 % +1 % +8 %

Ranking -04 4 5 2 3 1

Products - Focused on trans-port packaging for FMCG

- Die-cut - Inliner/American boxes

- Corrugated sheets

- Focused on creat-ing a total packag-ing solution for the electronics industry - Transport packag-ing

- Die-cut - Consumer pack-aging

- Non-corrugated materials

- Focused on high value added prod-ucts for the local spirits industry - Die-cut - High-quality pre-print

- Focused on con-sumer packaging for the local food-/confectionary industry - 25 % consumer displays

- 75 % corrugated packaging - 60 % pre-print - 30 % post-print - 10 % non-print - Majority of corru-gated is die-cut (75

%)

- Focused on the small-/midsized customer - No specific prod-uct focus - 8 % corrugated sheets

- 39 % Inliner/

American boxes - 48 % Die-cut boxes

Industry

Customers - Main customer segment is FMCG/food - 5000-6000 poten-tial customers - 600-700 actual customers

- Top 40 customers accounts for 75 % of Alfa’s volume

- Main customer segment is Elec-tronics

- App. 5000 poten-tial customers - App. 100 actual customers - Top 8 customers accounts for 83 % of Beta’s turnover

- Main customer segment is the spirits- and related industries - 55 % of turnover is in spirits (7-8 companies) - Top 4 customers accounts for 48 % of Gamma’s turn-over

- Main customer segment is food/confectionary - App. 350 actual customers

- Top 20 customers accounts for 80 % of Delta’s turnover

- Main customers segment are FMCG and Industrial - App. 6000 cus-tomers buys directly (24 000 buys through retail org.) - Focus on small-/midsized custom-ers

Competition - Top 5 suppliers accounts for app.

84 % of domestic sales (SCAP 11 %) - 4-4,5 % annual market growth

- Top 5 suppliers accounts for 96 % of domestic sales volume (SCAP 9,6

%)

- 12 % average annual market growth

- Top 5 suppliers accounts for 67 % of domestic sales (SCAP 35 %) - 1 % market growth in 2004

- Top 5 suppliers accounts for app.

40-45 % of domes-tic sales (SCAP 14) - Annual volume increase of 2,9 % - Annual turnover decrease of 4 %

- Top 4 suppliers accounts for app.

90 % of domestic sales (SCAP 30 %) - 0,4 % market decrease in 2004

39The indexation compares the five units per year using the lowest performer that year as base (i.e. index 100). The row “Change” indicates the percentage change between 2003 and 2004 for each unit.