You're facing warehouse expansion. How can you secure the resources needed for success?

Start by conducting a thorough needs assessment to identify the specific resources required, including space, technology, equipment, and personnel. Develop a detailed business case highlighting the expansion's benefits, potential ROI, and alignment with organizational goals. Engage stakeholders early to gain support, focusing on how the expansion supports broader business objectives. Explore various funding options, such as internal budget allocations, loans, or investor funding. Leverage partnerships with suppliers and vendors for favorable terms on equipment and materials. Finally, ensure a skilled project management team is in place to oversee the expansion, keeping it on time and within budget.

Why am I expanding my data warehouse: a) great profits, b) planning for business growth, c) operational inefficiencies, d) all of the above? An operational audit to assess what's going well before taking steps to scale my current solution will help. This is a very important cross-roads. I am equally as likely to bring my data warehouse solutions in-house as I am to choose a more supportive and insightful 'software as a solution for everything' provider. As a decision maker at the enterprise level, I should continue to build strategic partnerships inside my organization to approximate the magical holy grail called systems integration, so that we can mutually benefit from our solutions provider, hardware infrastructure and knowledge base.

In my experience, budget and clarity on the needs explaining this budget request always simplify things out. Indeed, do not forget the additional running cost that will be linked to this expansion, or better, for whatever reason show the savings that you could link to the expansion. And for the next budget, try to anticipate these needs for expansion well ahead. If you can secure these fundings a year to several month before the ectual physical need, that will be that much time saved.

A cloud first approach is almost inevitable. The key though is to choose one of the Technology providers, that will serve your organization end to end from Data storage, transformation, reporting, AI features etc. A deep understanding and evaluation of the service that each provider supports is essential. Eg. if you intend to use Power BI and Microsoft AI features to access the data warehouse via reporting then go with Azure. Another consideration is to not persist all your data. Consider using some virtualisation tools that will provide value quicker without duplication. Here the computer cost Vs storage cost is an important consideration.

Change is paramount and an often underestimated in terms of effectiveness and time. For change to be accepted, it’s really important to establish the ‘wow’ factor nailing ‘why’ someone would move to a new system, the benefits, features improvements, future cost savings etc. The before and after experiences should bring users along the journey of experiencing the change, effective address of feedback and continuous improvement. Once the first set of users are convinced use them as a voice to influence others on the journey. Ultimately they have to own this change. One thumb rule is to reduce the time for parallel run of the old Vs new as much as you can. The longer the overlap, the less effective is the change.

To ensure successful data warehouse expansion: 1. Develop a detailed plan with resource needs and timelines. 2. Secure adequate funding and allocate budgets for necessary resources. 3. Invest in scalable infrastructure. 4. Assign dedicated teams with clear roles. 5. Use project management tools to track progress. 6. Conduct regular progress reviews and address issues promptly. 7. Maintain open communication with stakeholders.

I always keep en eye on usage and dark data. 1. Is the data mart created in the warehouse being accessed regularly ? 2. Is there adequate knowledge and support to enhance it to suit growing business needs 3. Connect with the new users and high hitters accessing the information ? 4. Are there data sets that are not being consumed. Although storage cost is not significant these days, there may be hidden information that could be derived. Therefore even conducting a hackathon on the dark data could help unravel some insights that were not found earlier.