Some data warehouse projects unfortunately don’t work out…don’t let yours be the next! Here are our top 3 reasons why data warehouse projects fail.
1) Poor Communication Between Business Units & Tech Team
Great communication is not only a key component of success in life, it’s a major component of success in any data warehouse project. A major – major – reason why data warehouse projects fail is poor communication between project stakeholders and the IT/technical team that’s developing and coding the data warehouse.
The technical team’s job is to listen to the business requirements of the different business units involved and then turn those requirements into technical requirements. The only way this process works is if the technical team has a deep understanding of their business and its related terminology, and what insights their company desires.
The technical team must ensure that it has clear answers to highly important questions like:
- What insights are we trying to gain from our new data warehouse?
- What information are we after to help our business grow and gain a competitive edge?
- What results are we looking for?
From our experience, great communication during project planning nearly always includes organized thinking and planning, full disclosure of important details, proper terminology, and empathy and honesty on both sides.
We’ve also experienced issues where the technical team doesn’t fully understand what the business units are desiring, and instead of ensuring they understand by asking good questions and getting good answers, often times the tech team will start building the data warehouse instead. And BOOM. Eventually a major roadblock or issue occurs and the project gets interrupted and possibly fails.
So the big takeaway? Don’t take your initial design meetings between business units and IT lightly. Great communication is crucial during these meetings if you want an outstanding data warehouse.
2) Underestimating the Scope of the Project
Underestimating the scope of a project is another major cause of a data warehouse project failing. This reason ties into the first. A common problem in struggling DW projects is that project stakeholders believe a project will (or should) cost less than it actually does. This is often true whether “cost” refers to money, time, or resources.
Aggressive deadlines can be instrumental in project success and certainly have their place in the business world and in IT projects like data warehousing, but these deadlines need to always be reasonable and agreed upon upfront by all stakeholders.
To add, the budget for the project should be reasonable as well. Going cheap on building a data warehouse is rarely a good idea, and it’s likely that a “cheap” data warehouse will cost you more in the long run.
To avoid underestimating the scope of the project, the technical team needs to do a great job of communicating how long the project will take and what resources will be needed. It’s vital that the tech team also manages everyone’s expectations properly, and ensures all stakeholders are on the same page.
3) Rushing It: Jumping Right into Coding
Our final top reason why data warehouse projects fail is a big one, especially for technology people like us here at Key2 Consulting, as it can be easy to succumb to the excitement of creating a new data warehouse without having all the necessary resources and project plans in place.
The passion is great, but the outcome often is not. Project design should be fully completed and vetted before precious money and time is spent on coding. Rushing into coding should never be done.
Take this analogy. Let’s say you’re building a new house. If you want to be happy in your new home, are you going to tell the builders to start building without telling them how many rooms, bathrooms, floors, etc. you want? Of course not! You’re going to tell the builder as much as you can about the type of house you want. The more you can tell the builder, chances are the more you’re going to like your house.
And so it is with data warehouse projects. The more detail and explanation on what’s desired, the clearer the objectives are and the better the project will go.
Final Note – The Power of Synergy
One last point we want to make is that if you are able to properly handle the issues outlined above – communication, properly estimating the scope of the project, and not rushing into coding, chances are you are going to have a great project, because these elements really work well together. Good communication leads to a good understanding of the scope which leads to not rushing into the project!
Do you need help with your data warehouse?
If you need assistance with creating a new data warehouse or assessing/customizing your current environment, we can help. Contact us via our contact page and we’ll be in touch shortly!
Questions?
Thanks for reading! We hope you found this blog post to be useful. Do let us know if you have any questions or topic ideas related to BI, analytics, the cloud, machine learning, SQL Server, (Star Wars), or anything else of the like that you’d like us to write about. Simply leave us a comment below, and we’ll see what we can do!
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Key2 Consulting is a data warehousing and business intelligence company located in Atlanta, Georgia. We create and deliver custom data warehouse solutions, business intelligence solutions, and custom applications.
The article addresses several important reasons why data warehouse projects fail but does not mention a lack of coordinated and managed project testing. The experience of many on such projects is that most testing is being done by developers, business analysts, and data analysts – with little involvement by a process managed by trained QA testers.
The result is often poor data quality, missed defects, and unmet requirements.
Wayne,
That’s a great point and you’re completely right. QA is an incredibly important part of any successful data warehouse project and the process should always be managed by trained testers. Thank you for your comment!