IT Strategy frameworks are tools that help structure IT practitioners think through actions and investments into information technologies to accomplish specific objectives. They are used to analyze problems and develop strategies, tactics and specific actions to take to resolving these issues. The following frameworks are the key frameworks that we use to think through from a strategic level how we approach IT strategy.
The Problem
IT strategic thinking, decisions and implementation methods in the Pacific are typically based on very poor theoretical foundations. This leads to high risks of failures in programmes and projects.
Proposed Solution
Establish a set of common strategic management frameworks to help guide high level strategic thinking across disciplines
The following 5 frameworks outlined below are used to analyse and think through strategic decisions and actions.
OODA LOOP
What does it do?
Helps us understand how decisions are made and helps us diagnose where things may have gone wrong when problems arise
What does it say?
All decisions cycle through 4 separate and distinct phases. These are: Observation of what is happening in the environment; Orientation and understanding of what has been observed; Deciding what to do based on this understanding; Acting on the decision; These actions then have some impact on the situation and this is then re-observed and the cycle then repeats.
Helps us understand what type of systems we are dealing with and which management methods would be appropriate to apply to each system
What does it say?
There are 3 types of systems, Ordered systems, Complex systems and Chaotic systems. Each one needs to be managed differently. Ordered Systems can be further split into Obvious / Common Systems and Complicated systems.
Helps us map and understand what an operating environment looks like and where we should be investing our resources
What does it say?
All things evolve through 4 distinct phases driven by supply and demand competition. For technology these 4 stages are: Stage 1. Scientific Research is conducted into a some phenomena to understand it, Stage 2. Using the understanding of this phenomenon, tools are created to harness this phenomenon to solve some real world problem Stage 3. If valuable (demand side), more and more of these custom built solutions are created (supply side) and a market begins to from. As the market develops competition begins to intensify and then stabilise around a common design and the solution becomes a mass market product with very little differentiation. Stage 4. Eventually the solution becomes so standardised and commodised that it becomes a utility service, taken for granted by the general population until it is no longer available.
Helps us understand if a particular solution should be implemented
What does it say?
All system designs MUST satisfy 3 conditions before implementation can begin Desirable – The solution solves enough of a problem for people that they are happy to allocate resources to its development and maintenance Feasible – the solution can be implemented with the allocated resources Viable – the solution can be sustained long term because the revenue streams exceed the cost structure of the system
Helps us understand and communicate the scope of a government system as well as the order in which it’s constituent components need to be implement and why they need to be implemented in a particular order
What does it say?
All governance systems have 3-axis in which scope can be understood. These axes are the Governance Domain, these are the places where constraints can be imposed on a system to influence the behaviour of the entities operating within it; Governance Functions, these are the tasks that are carried out by governments to ensure the entities adhere to the rules; Governed Entities, these are the entities whose behaviour we are trying to influence
Helps us understand how to architect a data warehouse system.
What does it say?
Data marts are repositories of data belonging to particular lines of business. The data warehouse is simply a combination of different data marts that facilitates reporting and analysis. Based on Ralph Kimballs “bottom up” approach (Note that this is in contrast to Bill Inmons “top down” approach, (i.e. the Data warehouse is the centralised repository, data marts are created from it)