Before one proceeds onto further stages in the project scoping and planning, it is important to understand the dynamics of the organization, which will impact the method of progress. Readiness is measured on following counts:
| Factor of readiness | Low Readiness | High Readiness | Approach for the project in low readiness state |
| Buyer vs. Seller market | There is no perceived need for Data Warehouse. The CIO OR a solitary business owner has to place a lot of effort to sell the concept | The organization and the key decision makers are thirsting for this initiative | Increase the Project scoping and planning effort. Conduct a proof of concept without too much business involvement. Find the ways to limit the rigor expectations from the management. Ensure an early win. |
| Strength of Data Warehouse Sponsor | Least impacted by initiative, least in his priority list, and not a heavy weight | Heavy weight sponsor with Data Warehouse initiative among his top priorities, is Data Warehouse savvy and a recognized change manager | Try to change the sponsor. If not, Establish a steering group, which should involve some heavy weights Do more regular updated with management team to get a wider involvement |
| Business and Technology partnership | Business and technology on us vs. them mind set, technology not having adequate business knowledge OR perspective | Business and IT strong partners, and IT analysts working as part of business teams | Form a core team and make the rewards linked to team achievements.
Ensure that the analysis work adequately involved business users.
Increase training, team building and project management estimate. |
| Application Topology | Large number of applications and dispersed processing. Applications only partly owner by IT | A well managed IT portfolio and well groups processing platforms | Increase entire Extraction and Transformation estimate. Initiate the Data Mart taking data from the applications owned by technology and has a logically grouped processing. |
| Data Topology | No Data Standards, not centralized data dictionary, data model | Centralized and well managed Data Standards, Models and Dictionaries. | Increase Extraction and Transformation estimate. |
| Technology Topology | Varied platforms including legacy to latest RDBMS and multi-tier architectures | Most of the applications on standard application platforms | Increase Extraction and Transformation estimate. Initiate with Data Mart coming out of a single application technology platform. |
| Data Warehouse Technology | No existing Data Warehouse platform OR administration skills | The Data Warehouse project is going to be riding over the available Data Warehouse technology | Increase modeling, architecture and implementation effort. |
| Data Warehouse Experience | This is the first Data Warehouse initiative with the organization as well as the people involved. | Organization has already had Data Warehouse initiatives, OR have people who have handled Data Warehouse initiatives | Increase project scoping and planning effort. Increase business requirements and specifications phase effort. |
| Management culture in context of analysis and decisioning | Mostly Gut based OR ad hoc decisioning despite lip service to the facts and figures. Data, even if available, is not used. Perceptions and charisma are driving factors | Highly information and analysis driven decisioning | Increase the implementation and institutionalization effort. |
| Management Culture in terms of cross- functional team-work | Business planning and performance review is done only at a unit level. CEO is the only thread combining the business units. No organization level change management OR project management structure. | Highly cross functional work-groups. Central business planning and change management roles. Shared team and enterprise level targets. | Increase the project scoping, management and deployment effort. Start with a data mart involving a single business unit.
Ensure that there is a heavy weight sponsor. |
| Absence of a well documented Strategy to Business Goals to Metrics linkage | There is no strategy at organizational OR unit levels | Well documented strategy leading to goals leading to metrics | Undertake a quick session with the sponsor OR a core team on the strategy to goals to metrics linkage. In the list of themes, mark the areas where there is a confusion on the linked strategy OR business objective. |
