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Following is an approach for those who are sound now and able to rapidly maneuver later. This might work for service providers currently generating free cash or ISVs with strong market share and agile platforms. You wait it out and then follow the winning early strategies. However, like guessing, this is often a fall back used by weak management teams who will not invest in good strategy even when they are confounded by the current market conditions. These unfortunate service providers end up getting duped by vendors and ISVs and wasting millions. For the weak-minded ISVs, they simply fail.
Scenario Planning, as a formal method such as used in Cortney’s 20/20 Foresight, is effective. Cloud app ecosystem markets seem to be expressing what he calls "level 4 uncertainty", aka true ambiguity. In this domain, scenario planning can "help managers envision the possible" and think outside the box. Backward chaining causality, discovery of analogous situations, and documenting necessary belief statements are used to get a handle on available choices.
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Service providers with fewer resources must decide: ‘Win the Platform’ or ‘Win the Apps’? Build their own app store or attract app ISVs. |
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returns from apps (for example, direct and indirect revenue, good will, market stability). This can also help in developing hedging strategies for this market of apps, platforms, and clouds and determine the tipping points for the “following” approach.
With any strategy we need a few basics. Some basic market research would be helpful. What are the uptake curves on apps? Are there critical thresholds after which an app goes viral and below which it dies? What roles do early acceptors play? Who are the market darlings and market makers? Which real apps are in which categories? Which apps use the cloud and how are they performing?
It is also clear that some metrics will need to be discovered, developed, or decided upon.
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Fuzzy marketing methodology, Game Theory and decision analysis are formal methods that involve building static and behavioral models of the environment. These may not always generate a clear answer but they always generate a clear understanding between ‘what you know’ and ‘what you do not know’. Sometimes they can even tell the value of discovering an answer to ‘what you need to know’. One can narrow the choices to the point where guessing is profitable and not suicidal. In the best case, prediction is a systematically reached ‘best guess’ based on analysis of environmental trends and competitive behavior.
Complexity analysis is very new and so far mostly used in finance. Mapping the actual dynamics of the complex cloud/app market ecosystem is currently beyond us. But, combined with fuzzy/game/decision analysis, this approach can map the territory and greatly narrow choices. I think the most useful techniques here are the development of abstract accounting systems to rate and generate nontraditional and traditional market
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Developing common metrics is critical to developing a common industry strategy to align return with performance. In general, the industry will need to develop common strategic goals and policy to reach these goals. This strategy will be different from that set by individual companies, but the tools to get there are the same.
Futures
Sometimes it is not clear to my readers whether I am assessing current conditions or predicting future conditions. Whether I describe reality or advocate for a specific possible future. Let’s clarify.
The reality is that current definitions of the cloud ecosystem are not productive for formulating good strategy for service providers, OSS/BSS vendors, and big platform companies. Developing an ecosystem definition that services and aides us in strategy is imperative. I propose we use the structural approach of network appliance,
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