Business Portfolio Design

portfolio business design

Design of product and business portfolio Portfolio modelling has become more accepted as a result of the US corporate diversity trends in which firms are extending their production ranges and opening up new fields of business. Perhaps General Electric is the best known of the exponents of the portfolio view. There are two general types of model - the standardised ones, which tend to focus on growing and gaining ground, and the tailor-made ones, which provide more flexible responses to the scale by which they measure up.

It describes seven stages to be followed when assessing an established portfolio modelling or developing a stand-alone approaches. Within our intricate business landscape, large and small businesses continuously evaluate the interoperability of their strategies for each and every business unit or services - whether they exist or are scheduled - with the company's needs, capabilities and goals.

Shall we be in this business? Shall we have a new business to join? What can we do to gain and maintain a significant part of the global population? When looking for an answer to such exploratory question, many organizations consider a decision about the portfolio of products to be a portfolio decision. An enterprise provides a wide range of products that each require a specific level of capital expenditure and promise a specific ROI.

From this operational perspective, the top management's part is to identify the portfolio's constituent assets (or businesses) and allocate resources to them on a rationally sound footing. In recent years, a number of portfolio model tools have emerged to support managers in this work. For example, the growth/share matrices, the business profiling matrices, the business assessments arrays and the directive policies matrices.

Annex I lists these four and five other successful series. Conceptionally the different types differ in three points: No matter whether the business case provides a general descriptive frame or a frame designed to meet the needs of the business and the needs of its top people. Measurements used to build the style.

This is the level to which the paradigm prescribes regulations for the distribution of resource among product. Appendix II presents a comparison of the nine illustrated portfolio methodologies according to these three features. It is the issue faced by managers which strategy, if any, should be chosen. Insofar as the results of the modelling are the same (strategic guidelines), the choices may not play a role.

Recently, however, one of us recently likened three of these to each other and found that a number of different types of items can be classed differently according to the type of machine used. More worryingly, however, classifying your goods may also be dependent on the measurements that a dimensional design and evaluation of your goods uses. However, the importance of the valuation aspects of portfolio analyses can already be seen in the brief consideration of the various sizes and definition that use different methods.

However, it is surprising that most of the portfolio-related literature has not concentrated on the basic questions of defining and measuring, but on the sale of one or the other of these approaches and on the policy implication of, for example, the "dog" or "cash cow" state of a particular commodity. Our claim is that when choosing a portfolio strategy or assessing an existing one, managers should focus more on the design of the portfolio strategy and the likely sensitivities of the results (and hence the policy conclusions) to the dimension used and its actions.

Choosing the right dimension (and a thorough assessment of their actions) is a crucial issue. Analyzing a portfolio of products involves seven essential steps: Determine the plane and unity of your analyses and determine which compounds you are connecting. Identification of significant dimension, as well as individual variables and compound. Determination of the importance of dimension.

If two or more dimension are considered dominating, a corresponding array is constructed. Localization of local markets or transactions according to the portfolio dimension. Projection of the likely location of each and every item or enterprise on the dimension when (a) no changes in the enterprise's environment, competition or strategy are anticipated and (b) changes are anticipated.

Select the required location for each legacy and new franchise (as a foundation for the development of alternate strategy to bridge the gaps between the legacy and new franchises) and decide how best to allocate resource to these franchises. In spite of their appeal as ready-to-use remedies, standardised directives such as "all-out push-for-shares " and "hold position" are very risky.

When a recipe disregards pertinent dimension or the predicted company location under alternate scenario, it will be very deceptive. The portfolio analytics can only be an efficient tool for the analytics and evaluation of strategy choices if it uses the creative and imaginative power of senior managers - instead of following a general recipe. What should be the company levels at which the assessment should be carried out?

In the ideal case on all strategical business floors. It should also cover each and every item at the bottom tier (preferably by its positioning) according to markets. Conversely, the aggregate of commodity markets may result in them falling into a deceptive'average' portfolio exposure, which in turn may lead to inadequate policy interpretation.

Let us consider the case of a producer of (inter alia) shampoos, razor creams, soaps, toothpaste and other bodycare products for which a unique SBU (SBU) is in charge. It has established a growth/share index which this SBU refers to as Cashflow. Now this name can clearly be unsuitable for each line in the mixture and furthermore for each article in the line.

Therefore, aggregate data can result in incorrect portfolio positions, bad asset allocations and bad strategic advice. Portfolio hierarchies would begin at the line tier (or category or division) stage, go from the SBU tier to the SGE tier to the Group tier, and peak at the Group tier, which of course would encompass all sub-portfolios.

It would allow to evaluate relevance policies at the different analytical layers and help to identify and allocate resource to SGE' and production-line. The General Electric portfolio is based on a five-step approach: products, line of products, markets, SBU and business unit. While such a hierarchical structure is a significant enhancement over a portfolio for the whole enterprise, the complexity of today's business, especially in terms of large enterprise competitiveness (increasingly at the international level), suggests the need to develop a double hierarchical structure - national and world.

In addition, both hierarchy levels should not only be investigated for competitive models between brand and company, but also for possibilities for co-operation. What kind of company or business should we consider as a candidate for a M&A? In terms of the analytical layer, the required degree of differentiation is the degree of segments and positions of the products.

The portfolio should first be analysed in each pertinent sector and every pertinent portfolio item, then at higher level across the positioning of the different pertinent products and eventually - if the firm is a multi-national - country and access mode (such as exports, licences and JVs). At what point does it make sense to split the overall markets into sectors?

Responses become complex when frontiers are not easy to identify. There is a high degree of aggregation potential between different markets and different positions. For the superordinate portfolio view, a step-by-step positioning/segment portfolio overview is required. In the absence of them, the value of portfolio recommendation at company levels is doubtful, especially if the entities are diverse in terms of perception of their position and proposed marketsegments.

Conventional portfolio analytics tends to focus on consumers and focus on service delivery. Neither of the two main areas of focus are alternative, but supplementary diagnosis instruments. Once the portfolio managers have added the second layer of survey market to their portfolio analyses, they should assess and agree on the most appealing combinations of commodities and market.

Identifying a product-market portfolio and then selecting targeted countries and commodities is in line with the approach and results of merchandising fragmentation, suggesting that aggregate demands for each commodity vary by sector. Therefore, choices about allocating resources should not be confined to allocating them to specific commodities, but should also take into consideration trade-offs when making investments in different sectors of the economy.

Where the sales system occupies an important place in the company's overall market strategy, managers can expand the scope of the sales analytics to sales as a third domain. Naturally, the purchase or creation of new sales offices is often used to enhance a company's portfolio. In general, the portfolio should be structured in such a way that it includes all the essential choices that managers have for the use of their assets.

Where this is not the case, it should consider a reorganisation in which resources are allocated at portfolio level and unit level. Our most commonly used portfolio approaches are geared to our size of business and our size of our markets. Conversely, the Directorate General Policies Matrices are built on the viability of the industry and competitiveness, while the Products Performances Matrices allow the choice of other scales that are considered appropriate by managers.

There are four standardised portfolio schemes based on a grid where one axle shows the power of the products or businesses in relation to size or a wider feature, while the other axle shows the appeal of the sector or markets. They use two sets of measurement approaches: one based on a unique measureable criteria along each axle (e.g. comparative equity and incremental value ), the other based on compound measurements composed of a set of physical and physical determinants to identify each axle (e.g. business power and industrial attractiveness).

Of course, the elements that determine the extent of the interconnection differ between enterprises and even (although not often) between different enterprises of the same enterprise. Of these, six determine the sector's appeal - scale, value, profitability, cyclicity, recovery from global warming and global reach - while nine determine business power. In turn, the business strenghts consist of two components: the commercial standing (domestic and global shares, increase in shares and shares in comparison to the dominant competitor brand) and the commercial standing, which is determined according to the lead in five aspects (quality, technological, financial, marketing aspects and comparative profitability).

Of course, the members of top managers who choose the portfolio sizes expect them to choose sizes that relate to their business (and therefore portfolio) goals. Does it have to do with the advantages of the learn-behind, both in terms of large companies' ability to produce large amounts of goods and services and economies of scales, or with the fact that many large equity goods are competing on a non-price base, thus generating higher profit and margin?

In addition, industry surveys, such as breweries and banking, have shown that the ratio of PIMS's proportion to viability is not the same. Regardless of the ratio between loss of equity and gain, it is important to analyse not only the ratio between equity (and its measures) and return, but also the ratio between a variation in equity (i.e. return on investment) and a variation in the resulting return.

There is even less evidence of the link between part of the overall portfolio and the responsiveness of the products to the markets. In addition, this relation implies the importance of evaluating the responses of the different corporate brand names and, if not strictly related to another portfolio size, taking flexibility as one of the portfolio sizes.

Prior to entering into an exisiting portfolio of products or creating a new one, managers must identify the dimension they wish to use. One should not underestimate the importance of working definition for the dimension choices, both for the individual variables and for the composites. Individually adjustable dimensions: Consider a proportional proportion as used in the growth/share matrices (the most remarkable example of measuring one-variable dimensions), and then benchmark it against other possible proportion measurements that rely on it:

Define products (product line and brand in different shapes, dimensions and positions). Define the supplied geographic area, defining the competition area ( competitor, client and technology) in which the products are distributed, as well as the geographic, canal, client segments or exploitation area. Type of nominator in the stock computation.

a) all marks in the relevant markets, whether or not they are identified by the type of products or preferentially by the perceptual location of the mark; or b) a select number of marks - an optional set comprising all marks within a single subparagraph (such as domestic marks), the lead rival or the lead two or three rival.

The third type of concept, which is less liked but more conceptionally defendable, identifies the common denominator based on all those items that serve the same consumers' needs or solve the same problems. It is clear that a distributor has to make some crucial choices before choosing a defined proportion of it. Consider at least four different sizes of turnover: total levels, percentage rates of increase, levels by sector or category and percentage rates of increase by sector or category.

Combined dimensions: Multiple portfolio modeling uses compound planes to define matrices axles. For example, the Business Assessments Arrangement identifies one Business strength and the other Business Attraktivity area. "Everyone is a union of a number of unbiased and unbiased elements. This is because the main determinants of factor and importance are consumer behaviour, type of products, sector, company attributes and managerial preferences.

In contrast to the growth/stock/ matrix approaches, portfolio model with compound sizes strongly relies on the judgement of senior managers to pinpoint key drivers and measure their comparative importance. Whilst this is a sound outcome of strategy thought, it also places significant challenges on leadership times, unlike the Growth/Share Framework. There are other constraints to dimensional composites:

Assume a producer assesses three commodities according to a compound size (e.g. business strength) that consists of two elements. Clearly, the features differ significantly. However, with this special compound size (with the same importance of the two factors), similar items in the portfolio matrix would be allocated to the product. Shall we look for a consensual way, like a Delphi way?

Shall we even rule out the controversial element from the study? The use of a system of weighing that does not take into consideration strong links between elements may lead to confusion in terms of classifications. The same applies if no specific ball point is used to obtain the total number of points. When the enterprise uses five revenue measures and one level of production technologies to determine business strength, the comparative importance of the two is not 5 to 1; when the importance of the combination of those five elements is to be measured by empirical methods using the historic relationship between the elements, the computation represents a large amount of information because the nature of the statistic requires either repeated regulatory review (if a dependant element can be identified) or component review.

The majority of portfolio matrixes, such as the growth/share model, are based on an equivalent weighting for the dimension. We have already said that in compound dimension the coefficients are often weighed, but it is rare to put difference coefficients on the two main dimension that make up the array. On the other hand, most client specific portfolio formulas, the Analytical Hierarchy Model (AHP), allow weighting to be assessed by senior managers.

It was used in the development of other client specific portfolio model to evaluate the weightings associated with the risk/return dimension and other significant dimension. Those choices should not be entrusted to those employees who are engaged in building or implementing the portfolio. Portfoliomodels differ to the extent that they provide a general, inflexible and prescriptive frame or a variable form that reflects the properties of the users.

Equity/growth frame is the most inflexible, followed by risk-return models (taking into consideration the difference in managers' trade-offs between risks and returns). There is flexibility in both the directive policies matrices and production output matrices - the former in the determinants of dimension and the latter in the number and definitions of dimension.

A 2 2 or 3 3 matrix's ease of use makes it very appealing. However, it becomes simple and deceptive when (a) it disregards important factors and the circumstances under which the suggested policy is most likely to be successful, or (b) the grouping of continual variable such as equity or economic expansion into two or three groups results in the forfeiture of relevant information.

Such restrictions do not make portfolio modelling appealing in matrices. AHP, the latest version, uses a hierarchy and allows full freedom in the choice of dimension. It is based on the graphical or mathematical creation of effective limits. For any portfolio analytics, the most time-consuming job is collecting information about the product or other element in the portfolio and its relative returns on the chosen dimension.

Analyzing this information demands robust information from corporate documents (such as revenue and profitability) and external information (such as audience shares, sector expansion and perceptions of positioning). When analysing the position of a product in the portfolio, should the dimension be based only on historic information or should it also mirror projections?

Numerous economic forecast methods are used to forecast the output of current commodities. One of the available forecast scenarios for new markets is the simulation test environment. Does the assumption of the method make much sense? 4. Speaking for the demon, they can help those who design the portfolio to make meaning out of the approaches and projects.

Of course, the most crucial part of portfolio analytics is deciding what changes, if any, are necessary. Unfortunately, most off-the-shelf portfolio model does not provide specific guidance for building an optimum portfolio. Standardised portfolio modelling is particularly suitable for analysing the relationship between business entities and product.

Simultaneously, by proposing simpler approaches such as "harvesting", the model can limit management's incentive to test alternatives such as positioning crops or opening up new national or global markets. In addition, most of the portfolio model currently in use, which is geared to established product-market relations, lacks guidance on how to manage business direction changes.

Those shells don't respond to such issues as: Which features should a new line of products have to compensate for the company's portfolio? At times, the way the portfolio is structured indicates an imprudent shift. For example, a business with a low level of penetration in a low growing money supply environment may be very appealing even if it has a low level of equity ratio.

Given that the growth/share index does not take explicit account of equity intensities, a pet can be regarded as an inappropriate prospect for sale. Similarly, a company that has been found to be highly attractive to the markets and also has a firm valuation franchise could achieve a good return on investment but not a good return on investment.

Top officials should not let employees generate strategic choices when designing the portfolio. Top executives often choose to present themselves as assessors, but their participation in the creation is crucial for the company. Employees who are developing the portfolio should implement a method of allocating funds that supports senior executives in allocating funds and materials to current and new parts of the portfolio.

There are two ways to allocate resources in a portfolio context: The General Electric business intelligence methodology that uses GE's Business Assessments arrays as a tool for classifying products. Organizations combine information from this business cycle with other information to create a single asset management modeling tool. Analytical hierarchical models that include a resources assignment algorithms in the portfolio models.

Which kind of approach? From its inception in the early 1970s, portfolio technology - together with related ideas such as the SBU and the asset allocation graph - has become the frame for strategy development in many diverse businesses. Now, the arts are so far along that they offer a diverse range of options to a diverse business when it comes to deploying or replacing such a system, which obviously better suits its needs than the present portfolio.

Allow for the integration of the conceptionally desired dimension of risks and returns as well as all other unconventional factors considered important by you. Helps to give yourself an edge over your competition who don't know the company's portfolio frame and can't "read" it to anticipate the company's strategy.

May provide specific guidance on how to allocate resources between portfolio elements. Although the top managers decide not to adopt an unconventional methodology (based on a cost-benefit analysis), an assessment of the portfolio model currently in use in the seven stages we have described should increase the value of the portfolio assessment and the effectiveness of the new portfolio building strategy.

George S. Day, "Diagnosing the Product Portfolio", Journal of Marketing, avril 1977, S. 29. A Simultaneous Equation Model of Corporate Strategy", Management Science, novembre 1978, S. 1611 ; et Jean-Claude Larréché, "On Limitations of Positive Market Share-Profitability Relationships : Integrating Social and Business Needs", Long Range Planning, October 1974, p. 2. 5. see Derek F. Channon, "Commentary on Strategy Formulation", in Dan E. Schendel and Charles W. Hofer, ed.

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