AnalysisoftheCompanysFinancialStrategy

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for purchasing/reconstruction/renewal of fixed assets. FCF in 2015 were equal to zero. In 2014 the meaning was witness they got bank loan for performance financing.

For estimating balance liquidity, I compared different balance sheet items. As it was said earlier, the balance can be stated as absolutely fluid if the following

inequations met:

А1 > L1

А2 > L2

А3 > L3

А4 < L4

These terms are completely illustrative for Valio balance, so it can be

characterized as fluid.

Table 2.2.1.9

Liquidity coefficients of Valio and FrieslandCampina in 2014-2015

Another method for solvency evaluating is liquidity coefficients analysis (Table 2.2.1.9). Valio coefficients witness that they can easily cover current liabilities both with quick assets, monetary assets and short-term investments. However, the negative tendency for coefficients drop is obvious. Unlike Valio, FrieslandCampina had inverse tendency for coefficients increase: despite that in 2014 all of them were beyond average, in 2015 all of them were within normal limits.

Financial capability analysis. According to the competitive analysis results, Valio was the most financially capable on yellow cheese market (Table 2.2.1.10). The increase of leverage in 2015 in 0.06 pp. was a signal of addition loans attraction

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in order to overcome imposed sanctions. According to open source data, Valio was going to ramp up the local production through the introduction melted sliced cheese production line and doubled production on partners’ plants.

Table 2.2.1.10 Financial capability results of Valio and FrieslandCampina in 2014-2015

Just like liquidity coefficient, FrieslandCampina tendency for increase is more obvious. The company was able to strengthen their position and independence from creditors through the grow of equity to assets and debt to equity ratios and the ability to sponsor their performance on their own.

Profitability analysis. In 2015 Valio was marked with the drop of all the coefficients (Table 2.2.1.11) which were under the normal limits.

Table 2.2.1.11 Profitability coefficients of Valio and FrieslandCampina in 2014-2015, %

Moreover, the return on equity and capital employed drop compared to 2014 was more than 40%, return on assets more than 30%. These results were not surprising as I mentioned earlier was among the most damaged by sanctions companies as they lost significant part of imported products and yellow cheese market share. They were also financially damaged as «Oltermani» was prohibited

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and they had not had its sale for more than 2 years. Part of production capacity was lost too which forced them to set up production at partners’ plants such as Galaktika.

FrieslandCampina situation was much worse as due to huge losses in 2014 and 2015 all the profitability coefficients are unsatisfying. The only average coefficient was ROCE (2014).

The most crucial financial analysis is the estimation of efficiency ratios, accounts receivable (AR) / payable (AP) in particular, assets and inventory analysis. Drop in AR turnover (branch average is within 0 to 61 days) can emphasize the growth of insolvency clients and other sales problems. It can also be a reason of the softer policy introduction casing payments delay aimed at market share increase. The slower AR turnover is, the higher necessity for additional resources for market extension is. Both companies had a drop in this meaning in 12 days, yet FrieslandCampina value is under normal limits.

The increase in AP turnover can signalize about faster payments are arranged. The decrease can be the reason for both payments problem or creditors policy change including new payments delays. AP turnover of both companies fastened, yet it does not mean they fastened their liabilities paybacks. Assets turnover ratio is an indicator which helps identify of all the assets usage regardless of its’ generation source. Beside this, the sales to assets ratio shows how many rubles the company gets from each ruble invested in assets. Not only financial performance but also solvency and

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liquidity depend on invested assets turnover rate both companies had this coefficient grown in 2 times. And in both of them the reason was revenue drop (despite FrieslandCampina assets increase).

Inventory turnover ratio (normal limits within 0 to 23 days) shows how many times within analyzed period the company used mean inventory stock. This coefficient demonstrates the commodity quality and effectiveness of its’ management. It also allows identifying the drawbacks of non-used, old inventories. The importance of this indicator is connected with the fact that the profit appears with each turnover time, in other words while commodity usage. The faster commodity turnover is, the more effective the production is and the less the necessity in current assets is. The drop of this coefficient in 1.5 times in FrieslandCampina and 3 times in Valio was also caused by revenue drop. Based on the conducted financial analysis of FrieslandCampina and Valio I can highlight the following similarities of financial strategies:

1)Commercial costs reduction (package, logistics, marketing expenses etc.). It is obvious that companies took steps for significant cost reduction on goods delivery, advertisement in mass media and magazines, retailers’ catalogues.

2)Personnel costs reduction. Both companies were forced to reduce not only personnel bonuses but also the staff in whole.

There were also several differences that must be highlighted:

Significant equity growth in FrieslandCampina and insignificant in Valio. Valio, unlike FrieslandCampina, do not have negative financial results and for that reason they are not in need of parent company financial support. Balance sheets and cash flows statement analysis allows concluding that FrieslandCampina invested in fixed assets. Unlike FrieslandCampina, Valio fall back upon partners’ manufacturing facilities and strengthen production.

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2.2.2 ABC and XYZ analysis of FrieslandCampinas’ clients and products

Within the external with direct impact analysis framework, the clients and debtors must be analyzed compulsorily. For that ABC and XYZ analysis must be conducted for highlighting clients with the major and minor sales contribution and sales amount variation. ABC-analysis is based on Pareto rule which is «20% of efforts provide 80% of result». If we transfer this statement into financial performance ground, we can advocate that 20% of clients provide prevailing company’s revenue.

For conducting ABC and XYZ analysis I collected data for sales amount for 12 months in 2015. All the clients were ciphered by distribution channels (retailers, HoReCa, distributors, wholesalers) in terms of confidentiality compliance: S01, S02, S03, S04, S05, S06, S07. Within ABC-analysis all the sales contribution results were categorized according to their revenue and sales amount share:

•If the revenue/sales amount share is less than 5% – С;

•If the revenue/sales amount share is from 5 to 15% – В;

•If the revenue/sales amount share is more than 15% – A;

A-group is illustrative of the biggest clients providing major share of revenue. These clients must get the biggest attention and cannot be ignored. B-group is illustrative of middle-size clients providing satisfying and stable sales contribution. C-group contains clients who purchase goods from time to time. These clients get the least attention as they do not have huge loyalty and do not desperate for purchasing.

Within XYZ-analysis, data was divided into 3 main groups according to revenue and sales amount variation.

•If the revenue/sales amount variation is less than 10% – X;

•If the revenue/sales amount variation is from 5 to 15% – Y;

•If the revenue/sales amount variation is more than 15% – Z;

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X-group is illustrative for clients with constant orders level. Their sales amount is easily to forecast, and deliveries are sustainable. Y-group is illustrative for clients with satisfying variation who tend to swerve off the average orders level. Their orders forecast is more complicated but achievable anyway. The last Z-group contains clients who have impure orders amount which aggravate their sales amount and orders’ forecast.

According to the conducted analysis, I got the following results which are presented at the Table 2.2.2.1 and 2.2.2.2.

AY-group clients (S01) are characterized by high share of both revenue and sales amount, yet the orders variation in above the average so it must be stabilized. The BZ clients (S02) are illustrated by satisfying revenue and sales contribution and the same orders and sales variation. They have stable order level; their sales amount

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is easily to forecast, and deliveries are constant. The sales amount has a perspective to be increased and orders variation to be lowered. S03 segment clients which are at BZ group by orders level and CZ group by revenue share can be neglected as the revenue share is low and the orders deviation is high. Finally, clients of СZ groups (S04, S05, S06 and S07) are described with low purchasing activity and high orders deviation. These clients are extremely complicated to forecast with not only orders amounts but also their frequency which negatively affects company’s performance from inventory purchasing to logistics. For sales amount increasing and stimulating I advocate loyalty must be lifted through new products and payment restructure introduction and orders deviation must be changed with minimum order amount.

In terms of internal environment analysis, it is crucial to analyze the main source of wholesale copy revenue - its’ product line. This must be done in order to identify the commodity groups with the biggest/lowest sales and revenue contribution and also orders variety. For reasons of confidentiality compliance, all the products groups were ciphered (HoReCa products, white cheese, yellow cheese, butter and etc.)

For conducting ABC and XYZ-analysis I collected the data about sales amount from January to December of 2015. All the products were divided into stock items groups: G10, G20, G30, G40, G50, G60. Within ABC-analysis they were also split into groups according to sales and revenue contribution:

•If the revenue/sales amount share is less than 5% – С;

•If the revenue/sales amount share is from 5 to 15% – В;

•If the revenue/sales amount share is more than 15% – A;

A-group is illustrated for «stars» these are the best-sellers and providing the highest revenue. These items should be under constant and proper control for keeping their maximal competitiveness. B-group is illustrated for «cash cows» or

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those which provides constant and satisfying sales. Finally, C-group includes outsiders, having the least revenue share due to various reasons.

Within XYZ-analysis each group were categorized according to orders and sales amount deviation:

•If the revenue/sales amount variation is less than 10% – X;

•If the revenue/sales amount variation is from 5 to 15% – Y;

•If the revenue/sales amount variation is more than 15% – Z;

X-group is illustrative of product items with constant orders level, easily forecasted sales amount and sustainable deliveries. Y-group is illustrative of items with satisfying deviation which generally swerve off the average orders level. Their orders forecast is more complicated, yet they are achievable anyway. The last Z- group contains products with rare and small orders which hard to forecast due to high orders deviation.

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According to the conducted analysis, I gained the following results presented in Tables above. The results for revenue shares and sales amount are almost the same. The lack of some items identity caused by market activity (discounts). It is obvious that the G30 item group is characterized with high sales share and low deviation. Due to that fact, prior goal for these group are orders’ deviation decrease and market activity control. G60 group by sales share is at AZ-group and by revenue at BZ-quadrant. That means that the top priority for that product items is orders deviation decrease and prices stabilization. G60 segment with the sales share is within AZ quadrant and by the revenue at the BZ group which means that the prices are usually discounted, and their stabilization must be done in line with orders’ level. G40 group has similar recommendations. G20 group is characterized with sustainable demand and its’ sales amount is easily to predict. For that reason, their share in revenue must be rocketed as much as possible. Within BZ quadrant by sales amount and CZ by share market activity, items of G20 must be taken under severe control, especially as the devotion is higher than the average. Finally, G50 is at the CZ quadrant so their revenue and sales contribution are extremely low in line with seldom and rare orders. The company should not decline this product, yet they should conduct several market researches to identify the main drawback leading to low sales amount. Trend lines are upwards which signalize about increasing profitability.

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Figure 2.2.2.1 Return on sales for each product segment in 2015, %.

The return on sales for each product group is presented in the graph above. G10 was omitted due to negative profitability, G50 was neglected due to zero sales in 1st quarter of 2015. According to this, all the items have a tendency to increase as their trend line go up from month to month. The most perspective group is G60 and according to the ABC/XYZ analysis its orders must be stabilized for achieving impressive sales and revenue increase and great financial results.

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