Evaluation of portfolio planning tools on the example of the Polish banking industry

  Strategic Marketing Evaluation of portfolio planning tools on the example of the Polish banking industry 07/05/2004  

TABLE OF CONTENTS

1  INTRODUCTION  1

2  ANALYSIS  1

2.1  Portfolio planning tools  1

2.1.1  The Boston Consulting Group Growth-Share matrix  1

2.1.2  The GE Market Attractiveness-Business Position matrix  2

2.2  Analysis  2

2.2.1  The Polish banking sector and LG Petro Bank S A.  2

2.2.2  Effectiveness of the BCG matrix in the Polish banking industry  4

2.3  Critical evaluation of portfolio planning tools  4

3  CONCLUSION  5

4  APPENDICES  6

5  BIBLIOGRAPHY  7

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Strategic Marketing Evaluation of portfolio planning tools on the example of the Polish banking industry 07/05/2004

The following report concentrates on the in-depth analysis of the Polish banking industry in general and LG Petro Bank S.A. in particular with the aid of accepted portfolio planning tools identified in contemporary relevant textbooks.

Two widely accepted tools are presented and their limits and constraints shown in a critical evaluation in the light of new perspectives and opinions found in journal articles and textbooks and also in the context of the situation of the Polish banking sector.

ANALYSIS

2.1 Portfolio planning tools

“The increasing rate of change in economic, political and social environments of business today has lead to growing competitiveness, uncertainties and risks and thus to a dramatic increase in attention given to strategic planning of all kinds. Marketing planning has itself received a good

¹ deal of attention.”

² portfolio planning models pursue two major purposes: According to Grant

1 to assess the position of a business in its industry together with the prospects for that industry over the medium to long-term.

2 to analyse the portfolio balance and suggest strategies for individual businesses in terms of cash flow, future prospects and risks.

2.1.1 The Boston Consulting Group Growth-Share matrix

³ is the Boston Consulting Group (BCG) Perhaps the best-known among portfolio-planning tools

matrix which defines two dimensions, market growth rate and share, to measure the

⁴ attractiveness of a product (or business) portfolio.

⁵ and The market growth-dimension (vertical axis) is used as a proxy for market attractiveness can be related to the product life-cycle. As every PLC stage suggests a different strategic

^{6 7} objective, i.e. build, hold, harvest or divest , this dimension serves as an indicator for ‘cash use’ .

⁸ This is In turn, market share (horizontal axis) has been found to be related to ‘cash generation’.

⁹ which suggests that as production increases indirectly related to the experience curve concept

cost saving effects will emerge. Another aspect is the Profit on Impact of Marketing Strategy (PIMS) study, which among other things suggests a strong relationship between high market

¹⁰ share and return on investment.

Combining cash requirements of market growth and cash-generation potential of market share in a two-dimensional grid four types of SBU and their appropriate strategies can be distinguished:

¹¹ Question marks, Stars, Cash Cows and Dogs .

¹ Turnbull (1989), p. 7

² Grant (1995) found in Hooley [et al.] (1998), p. 54

³ Kotler [et al.] (1999), p. 97

⁴ Hooley [et al.] (1998), p. 55

⁵ Jobber (2001), p. 254

⁶ Jobber (2001), p. 255

⁷ Hooley [et al.] (1998), p. 57

⁸ Hooley [et al.] (1998), p. 57

⁹ Hedley (1976) found in Wensley (1981), p. 175

¹⁰ Hooley [et al.] (1998), p. 57

¹¹ Kotler [et al.] (1999)

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2.1.2 The GE Market Attractiveness-Business Position matrix

The BCG matrix has been frequently criticised for its restriction to market share and growth rate

^{12 13} as the sole guidelines for strategic decisions.

In fact, business strategy is influenced by a multitude of factors. A more fundamental and comprehensive model for portfolio analysis was advanced by McKinsey in conjunction with

¹⁴ General Electric, called the Market Attractiveness-Business Position Matrix.

The first set of factors addresses the favourability of the market, the second refers to the business position in a market. All criteria are plotted on a 3x3 matrix depicting the relative

¹⁵ investment opportunity for a business.

¹⁶ Management has to decide which factors are applicable for the company’s products , i.e. what

¹⁷ makes a market strong and what makes i t attractive . Scores and weightings are assigned to

each factor and multiplied to receive a rating in respect of the two variables market attractiveness

¹⁸ and business position.

¹⁹ provide a grid with strategic guidelines for each of the nine squares of Johnson and Scholes

what they call a directional policy matrix; investment will be in the businesses with the highest growth potential and the greatest strength whereas the weakest and least attractive markets should be divested or harvested. The middle range section businesses need to be further evaluated on their position in the market and selective investment will be for those businesses

²⁰ with the highest pay-off.

a See appendix 2 for illustration.

2.2 Analysis

2.2.1 The Polish banking sector and LG Petro Bank S.A.

The Polish banking sector:

§ highly fragmented and undeveloped

§ undifferentiated range of banking products

§ low diffusion of services across the country

§ low acceptance among the population

LG Petro Bank S.A.:

§ young bank à presumably low national market share

§ strong regional position à possibly high growth potential in rural regions

§ focussed strategy to serve mainly energy and fuel establishments à possibly too narrow focus, limited growth potential

§ danger of market liberalisation and strong f oreign direct investors, i.e. international banking consortia to take market leadership in Poland

§ need for differentiation/establishing a competitive advantage

¹² Turnbull (1989), p. 13

¹³ Jobber (2000), p. 257

¹⁴ Turnbull (1989), p. 13

¹⁵ Hooley [et al.] (1998), p. 64

¹⁶ Jobber (2000), p. 258

¹⁷ Hooley [et al.] (1998), p. 65

¹⁸ Hooley [et al.] (1998), p. 67

¹⁹ Johnson & Scholes (2002), p. 289

²⁰ Johnson & Scholes (2002), pp. 288, 290

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