Figure 9 – Value Chains vs Evolution vs Characterstics
At first glance it looks fiendishly complex but in reality it’s rather simple. An organization consists of many value chains (such as the one shown above) with contain many different components all of which evolving. As those components evolve their characteristics change from more chaotic to more linear.
Many of the components will be common to different value chains i.e. a company producing multiple online software offerings each with their own value chains will find common components such as compute resource and power between them.
Now, not all parts of the value chain are equally visible to all. For example, from a consumer perspective, the parts of the value chain that are visible describe what is being offered. Hence in the case of Fotango this consisted of a web site, photo storage, payment systems and image manipulation.
Many parts of the value chain - such as what servers were used to provide compute, the electricity supplier for power - are invisible to the consumer.
Let us now consider the Fotango site – an online photo service. There were many equivalent sites at the time of its operation in 2001 that provided a means for the capture and sharing of digital photos. Many of these competitors were simple storage services and the provision of a web site, storage and payment system could not be viewed as a differentiator to these competitors.
However, the photo storage system (designed specifically for resizing and storage of images to useful photo sizes) and the image manipulation system (for removal of red-eye, filtering and various digital effects) whilst not unique were uncommon enough that they could be considered a differentiator with many competitors.
It’s these more chaotic activities (scarce, poorly understood, deviating from what existed before) that directly differentiate competitors in terms of what they provide. However those less visible, lower order (i.e. further down the value chain), more linear components still have an impact but in this case it is indirect.
Take two competitors with identical value chains and service offerings. If one competitor had a much higher cost of provision of a lower order components such as compute then this is likely to manifest itself in the price of the overall offering. Hence there is an indirect impact of these less visible (to the consumer) components from cost to reliability. This distinction between direct and indirect impacts on the offering is shown in figure 10.
Figure 10 – Value Chain, Visibility and Offering
To the supplier (i.e. Fotango) perspective then obviously all the components of their value chain were visible. The consumer might be concerned about the offering, how it is differentiated from competitors, its cost and reliability but the supplier is concerned with all the components that create this effect (what supplier to use for servers, power etc).
From the supplier’s perspective, the more linear activities (compute resource, electricity) were a cost of doing business and the focus had to be on operational efficiency. Any inefficiency impacts ability to compete on price and therefore to survive today.
Those more chaotic activities (online photo storage, image manipulation) that are potential differentiators with competitors influence how much the consumer will value the service over competitors. An inability to effectively manage and create those components would limit the ability to differentiate and hence survive tomorrow, as the site would be seen to lag behind the market.
Hence the supplier has to strive to be more efficient with those linear, cost of doing business activities whilst simultaneously differentiate with those more chaotic activities. The supplier has to be both efficient and “innovative” (as in creation of new activities).
The fiendish part comes into play when you think about how do you manage this spectrum of chaotic to linear. For example, take the online image manipulation system that Fotango created. It was a new concept for which few other examples existed. Being more chaotic, it was constantly changing, deviating from the past and experimentation was the order of the day. Any management technique had to allow for this and hence a project management technique such as Agile development was most suited.
However, if you take the implementation of Fotango’s customer relationship management system (CRM), then this was in a more linear phase. It was more commonplace, many companies had done this and the concepts behind CRM were well understood. In this case a more structured technique that attempts to eliminate deviation and repeat past success is desirable. Candidate techniques would be Six Sigma or Prince 2.
The polar opposite characteristics of chaotic and linear means different techniques should be used. A technique that attempts to eliminate deviation (such as Six Sigma) will never be as effective as one that enables change (such as Agile) for an activity in the chaotic phase and the reverse is true for the linear phase (see figure 11)
Figure 11 – Management Techniques and Evolution
Hence in order to survive today (by being operationally efficient) and to survive tomorrow (by creating enough differentiation through novel activities) then polar opposite techniques are required. This is known as the Salamon and Storey Innovation paradox.
Unfortunately, we have a tendency in management towards a one size fits all solution. If we find that Agile development is successful in some quarters (such as an image manipulation project), we assume it is suitable for all (such as installing a CRM system). This pursuit of the one size fits all causes endless debates of the form Agile vs Six Sigma.
This problem is only compounded by activities themselves not remaining static but evolving. Hence a technique that was once suitable for a specific activity at some point in the past may not be so today. For example, if we roll the clock back on CRM there was a point when it was not commonplace, not well understood and provided more through custom built systems. Hence in the past, an Agile approach would have been more suited.
There is a reason why we probably tend towards this belief of one size fits all, it’s our desire for simplicity. Ashby’s Law of Requisite Variety (a staple diet of those interested in cybernetics) describes how a management system needs to have as much variability as the system being controlled in order to be effective. There are two solutions to this problem, either you enable management to be complex (using multiple techniques depending upon what you’re dealing with) or you pretend that what is being managed is simple (i.e. one size does fit all). Our desire for uniformity points to our tendency to do the latter.
Fortunately our one saving grace is our competitors. Whilst adopting one-size fits all approach will impact either efficiency or “innovation”, the impact is nullified if our competitors do the same. Our problems only occur when a competitor uses multiple techniques and hence is effective at both extremes – being more efficient at the linear and more “innovative” with the chaotic.
The above was one of those general lessons that we learned in the software industry almost a decade ago. With Fotango, we had undergone the typical yo-yo from highly structured methods to more agile techniques in 2002 and the realization that both were needed by around 2004. It has become increasingly common for companies to use multiple techniques depending upon what they are managing but debates of the Agile vs Six Sigma do still occur.
In a survey of over 100 companies undertaking in 2011, with companies being categorized as more traditional or more next generation (the leading edge of web 2.0), the distinction between use of single specialized methods (e.g. Agile or Six Sigma) or use of mixed methods is shown in figure 12.
Figure 12 – Single or Multiple methods by company type.
Over 85% of next generation companies used multiple methods (i.e. they were neither Agile nor Six Sigma but both) whereas 40% of traditional companies tended to specialize in one.
In the above section, I have mainly talked about software activities, similar one size fits all approaches can be found throughout other functions of the organization. This is despite each function (whether HR, Finance, Marketing or Operations) containing masses of activities that are all evolving.
Before we leave this section, it is worth reiterating some of the main points.
1. Organisations can be described as a set of value chains that contain multiple component activities.
2. Those component activities are evolving from genesis to commodity and this is driven by competition (both consumer and supplier).
3. As those components evolve their characteristics change from more chaotic to more linear.
4. The techniques needed to manage an activity vary with that change of characteristics which is why one size never fits all.
5. Failing to manage those components effectively can impact our chance of survival today (due to cost inefficiencies) or survival tomorrow (due to lack of differentiation).
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