We need people in all layers of the organisation to design, build, execute and maintain the data strategy. it is clear that the leadership in the organisation has to provide not only the resources, but also the financial means to educate them and provide them with the effective tools and time to execute.
To execute the data strategy, the data steward, scientist, analyst, architect and engineer must work closely together. All assigned people must be available and competent. This requires an assessment of the knowledge, skills and competences of the existing employees, possibly resulting in further training or even insourcing of additional personnel.
The decisions for deploying in-house staff, hiring new staff or hiring third parties are not easy to make. Apart from the financial and time-consuming aspects, the scarcity of skilled and competent personnel on the market can also lead to project delays and high hiring costs.
It is clear that a successful data strategy requires a coordinated approach from IT, HR, Procurement and leadership departments in the organization.
Existing processes and policies probably need a re-design or update to continue support for business request and requirements. New processes and policies might be necessary for collecting, storing, distributing, and accessing data, in order to properly manage and govern the data flows between users, applications, and sources. Think about authentication, and autorisation for users of the self service portals, BI and AI tools, modern applications and more.
For the same reason the technical infrastructure or IT need to be assessed to determine what changes and amendments need to be made in order to continue and optimize support for business strategy, data strategy and related architectures. All aspects in the ISO model, related to technology and IT need to be evaluated and adapted to the requiremenst of the data strategy, so that all user data requirements can be met effectively. Obvious examples are migration to the cloud, sourcing pure technology or ready-to-use services, more bandwith to process more data, new tooling for BI, AI, and analytics application, faster mobile infrastructures to support more mobile devices and users, security features for home offices and much more.
Finally, we want to prepare you that you will never be done with all these improvements in people, technology and processes, because once you make the data strategy successful, it will automatically lead to more data usage, forcing you to adjust your data strategy, leading to … .