In an interview with a project manager at LEGO Corporate IT (CIT) we were presented with a problem regarding project evaluation and how lessons learned from these evaluations never seems to establish themselves in the organization and their work with project management. With this problem as a foundation we widened the focus area to work with this problem:
How can LEGO by means of business intelligence establish increased organizational learning in their work with IT projects?
To answer this we set up five work questions:
- What is organizational learning?
- How is organizational learning connected to business intelligence?
- Which factors can influence the success of a BI project in LEGO’s work with IT projects?
- Which needs should a BI solution fulfill to deliver an improved decision support?
- What could a possible BI solution look like?
To answer the first two questions we started out by creating the theoretical framework of this thesis, where we defined organizational learning (OL), knowledge, knowledge management (KM), business intelligence (BI), and how these concepts are interconnected. Through this we argued that BI can contribute to the process of obtaining knowledge, by providing information, which thus is transformed to learning, knowledge, and hereafter organizational learning, which all adds up to improved organizational performance. Furthermore we discussed the need for a KM-strategy to establish how knowledge and KM is handled in general, as we argued that BI should not be view as the sole answer, but as part of a solution.
Having answered the first two work questions we moved on to answer the next. We established our research tools with offset in Kimballs Life Cycle Toolkit (1998 and 2008). Through a modified version of Kimball’s readiness theory we analyzed LEGO’s readiness for a BI solution based on three factors: Compelling Business Motivation (CBM), Current Analytical Culture (CAC) and Feasibility. We found that LEGO should organize a change management initiative in order to increase the current state of readiness regarding especially CBM and CAC. As change management is delimited by this thesis we did not go further in depth with this. We did, however, define five terms that needs to be fulfilled in order to increase the readiness before the implementation of a possible solution;
- Business sponsors must be dedicated, agree on scope, and be realistic about the solution.
- Problems with motivation, decision making, and KM need to be taken care of.
- Agreement on definitions operating in the systems.
- Deployment of a central data warehouse.
- Project data is created from scratch.
To answer the fourth question we set off from Kimball’s theory on business requirements (2008) and thus analyzed the requirements of the business users. This produced a list of requirements which we categorized into three main groups: availability, relevance, and structure. Each category defines a general business requirement to the BI solution.
Having established the business requirements we were able to answer the fifth question and provide LEGO with a possible solution. This solution needs to include the terms previously stated to increase the readiness status. The solution is based on the idea that all project information shall be stored in a single data warehouse, and through this data can be read, modified, written, and deleted through web interfaces, including web formulas and web dashboards. We hereby recommend the deployment of a project database to store all information about projects in all its lifetime. Furthermore we recommend the deployment of an employee database, to be able to get information about employee allocation, experiences, and proficiencies. Through all stages of the project the project organization will receive fact based decision support from former projects, and hereby embed experience and knowledge from existing and ended projects to be used in all stages of new projects.
Finally, we concluded that organizational learning can be improved by means of business intelligences by providing a possible solution that employs project data from former projects to enable improved decision support in new and ongoing projects.
I did my oral defense of the thesis on wednesday the 13th of june, and the thesis received top grade, which is 12 in Denmark.