Management practices evolve overtime, as for instance the business environment changes and information technologies offer new possibilities. Yet, over the past 40 years since “Strategy” has been recognized as a practice of its own, one problem has remained relentlessly unsolved: How does one turn strategy into implementation?
Senior managers, scholars, consultants, all have offered solutions that may have been effective depending on a particular situation or leadership style, yet as of today, many top managers still wonder why it seems so difficult to execute on their plans, while operational teams feel their needs and priorities are not well understood by senior management. Disconnects often remain many despite best intentions on all sides.
One of the most widespread strategy tools today, remains the “matrix portfolio”, a bubble chart type usually segmented into four different quadrants. The chart is particularly information rich as it displays three metrics at the same time: In the example below, we can see “Margin%” vertically, “Margin% Change” horizontally, and “Revenue” being proportional to the size of each bubble. Bubbles beneath display product families for a distributor of ethnic food products. Green bubble families have above average and growing margin, red bubbles have below average and declining margin, while yellow bubbles are above average but declining.
Such matrices are well suited for financially oriented analysis and decision-making, for instance in the manner of managing a stock portfolio. However, often matrices are used to make decisions with operational impact, such as “that product family has been growing three points in margin% over last semester, let’s set a goal of an additional 2% for next semester”. Or “that red bubble is below average and in sharp decline, may be we should discard it altogether”. At a strategic level in a large company, product families will rather be product divisions, or business units and world regions.
Such matrices are well suited for financially oriented analysis and decision-making, for instance in the manner of managing a stock portfolio. However, often matrices are used to make decisions with operational impact, such as “that product family has been growing three points in margin% over last semester, let’s set a goal of an additional 2% for next semester”. Or “that red bubble is below average and in sharp decline, may be we should discard it altogether”. At a strategic level in a large company, product families will rather be product divisions, or business units and world regions.
Such key decisions, when they are mostly made on the basis of global data, may be misleading as they often don’t reflect the behavior of underlying entities. Henceforth rooted and pernicious problems in strategy implementation. Indeed, let’s now take a closer look at our “margin matrix”, at a detailed individual product level. We can see a very different picture than the original one on the global product family level.
All green product mini-bubbles for instance, belong to green product families located in the upper right quadrant; yet green individual products are scattered all over the four matrix quadrants. The same holds true for the other three quadrant colors and all global product families versus their individual constituents. The trouble here is that the scattering is not just innocuous. We are used to believe for example that if an entity is growing, most of its components must be growing too. In the above case study, an average of 40% of individual products does not belong to their original product family quadrant. So a green product family may be above average and growing in margin, yet 40% or more of its underlying products may be behaving otherwise, for instance declining. That is also true when weighting products by revenue: around 40% of total product revenue is earned outside of product family quadrants. That sets a very different picture than the usual global matrix portfolio. Thus, how can senior managers make well informed decisions, especially when they lack the time to take into account detailed data?
All green product mini-bubbles for instance, belong to green product families located in the upper right quadrant; yet green individual products are scattered all over the four matrix quadrants. The same holds true for the other three quadrant colors and all global product families versus their individual constituents. The trouble here is that the scattering is not just innocuous. We are used to believe for example that if an entity is growing, most of its components must be growing too. In the above case study, an average of 40% of individual products does not belong to their original product family quadrant. So a green product family may be above average and growing in margin, yet 40% or more of its underlying products may be behaving otherwise, for instance declining. That is also true when weighting products by revenue: around 40% of total product revenue is earned outside of product family quadrants. That sets a very different picture than the usual global matrix portfolio. Thus, how can senior managers make well informed decisions, especially when they lack the time to take into account detailed data?
Indeed, our research at EFFIS has shown that discrepancies between global and detailed business matrices are usually comprised between 30% and 60% or more. In order to account for such substantial numbers, we have introduced a new type of indicators that measure disparities between global and local. The “Intra share” is the part of the local that behaves like the global: here it is individual products that remain inside the same quadrant as their global product family. Opposite, the “Extra share” is the part of the local that behaves differently from the global, meaning here products that belong to a matrix quadrant different from the quadrant of their parent product family. Thus the Extra share is a measure of disparities between global and local viewpoints. In the above example, average Extra share amounts to no less than 40%.
In order to account visually for Intra/Extra share, we add to each bubble within a given matrix, a crown that signals Intra share in green and Extra share in red (as displayed just below). When Extra share is low, underlying data is rather homogeneous and global aggregates portray local constituents fairly. When Extra share is high, underlying data is heterogeneous and global and local viewpoints may differ markedly; when that is the case, drilling-down into detailed data is usually preferable, as well as understanding how Extra share may be split between different quadrants. Thus a red bubble with a lot of Extra share may be worth salvaging after all, as a large portion of its constituents belongs to more valued quadrants. While the growth of a green bubble may be jeopardized if a large part of its constituents are nevertheless in decline.
In our experience, that kind of visually guided data exploration is especially useful when there is complexity in a business model: several thousand products and/or customers, possibly many competing products and/or market segments, conditions found in the consumer goods industry in particular, but not exclusively. At the corporate level, a large company always deals with at least some areas of complexity. And within that context often lies the temptation to reduce complexity. One approach is to limit heterogeneity and thereby Extra share, recurring to the kind of business segmentation that unfortunately often leads to organizational silos that impede transverse agility and empowerment.
In our experience, that kind of visually guided data exploration is especially useful when there is complexity in a business model: several thousand products and/or customers, possibly many competing products and/or market segments, conditions found in the consumer goods industry in particular, but not exclusively. At the corporate level, a large company always deals with at least some areas of complexity. And within that context often lies the temptation to reduce complexity. One approach is to limit heterogeneity and thereby Extra share, recurring to the kind of business segmentation that unfortunately often leads to organizational silos that impede transverse agility and empowerment.
Such senior management issues are often key when trying to implement strategy, yet they are hard to grasp with adequate metrics. Qualitative judgment may remain invaluable, yet Intra and Extra share offer a new type of measures that are welcome in a management world that has transformed with the growth of analytics and ubiquitous reporting tools. If implementing strategy remains challenging as an art, it may also become increasingly successful as a science.
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