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Author Archives: berkeleythoughttrain
Designing supplier contracts: Asymmetric information
How does Rackspace, a hosting services provider, structure supplier contracts? Suppliers might have a fixed cost per unit but this information is not public knowledge. Rackspace must assume the probability supplier is low cost is ‘p’ and ‘1-p’ is the … Continue reading
Posted in Economics, Game Theory, Strategy, Technology
Tagged asymmetric information, game theory
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Are you a high-ROM manager? Talking managerial energy here
This is the first of several posts on a qualitative metric, return on management (ROM), that can be used to assess if your firm’s strategy implementation is on track. Why is it that a large percentage of the most reasonable, … Continue reading
IBM cloud for China Unicom
This post is inspired by my ongoing analysis of Rackspace, an up and coming provider of managed and hybrid hosting services in the cloud computing industry. The content of this post is based on my observations gathered while attending technical … Continue reading
Posted in Technology
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Walt Disney- contemporary strategy analysis
Walter Elias Disney entered the entertainment industry when he and his brother, Roy started a studio in Hollywood. He had, by then, already experimented with animating characters using newer “cel” based technique which was better than the contemporary “cutout” based … Continue reading
Rackspace Hosting: brief competitive strategy analysis
Cloud computing is a very competitive market with the main competition coming from AT&T, Verizon, CenturyLink (via acquisition of Qwest in 2010), Softlayer and British Telecom. Key success factors for a provider of cloud computing services a) Niche market b) … Continue reading
Congruence testing approach to security architecture
From management literature (Tushman & O’Reilly), the congruence-based problem solving is a method to quickly and accurately identify the root cause of performance or opportunity gaps. In the context of security architecture, the congruence model can be applied to creating … Continue reading
Maximizing profits when demand is known
Maximizing Profits When Demand is Semi-Log We want to maximize profits, or (P-MC)*Q. Our demand function is given as ln(Q) = aP + b. To get Q from ln(Q), we use the exponential function (since e^ln(x) = x): e^lnQ = e^(aP+b) … Continue reading
Posted in Economics, Strategy
Tagged demand modeling, linear demand, profit modeling, semilog demand
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Linear and log models for modeling demand
Price sensitivities of demand differ depending on the product and the market. We can model our demand function to reflect how we think quantity responds to price. The following post will use calculus. If you don’t like calculus, the important … Continue reading
Posted in Economics, Strategy
Tagged calculus, log-linear, log-log, price elasticity, semilog
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Google’s Android Revenue per Device per Year
In a Strategy for IT class, I had very interesting discussions with Prof. Reza Moazzami and peers about how Android’s fragmentation as a revenue source has hurt Google. I’ll write a more detailed post on how Google’s mobile strategy went south … Continue reading
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