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Enterprise Business Intelligence initiatives are often large projects that come with layers of complexity. 

There are many opinions and approaches for implementing, managing, and supporting these initiatives. And when they’re mishandled, they can be expensive and incur difficulty in reaching near and long-term business value.

Let’s look at three of the most common mistakes made during Business Intelligence initiatives and how eLogic helps our customers avoid them by prioritizing the most valuable data sets to get insights faster, cost-effectively scaling your solution, and ensuring the initiative is easy to support after launch.  

Mistake #1: Creating an Enterprise Data Warehouse Up Front 

When you design your data warehouse first, the scope of the master data requirements is enormous and complex. You end up using key talent, and your staff gets double or triple loaded in seemingly endless workshops and meetings. You also limit your ability to easily scale out because your warehouse was created before you defined your reporting or predictive modeling needs. As you identify new use cases, new data is required; often from other systems. This leads to redesigning, refactoring and additional testing – another unforeseen investment and delay to realize your analytical dream and real business impact.  

All of these make the complexity of the project greater, and with it raised costs and a longer time to value.  

How eLogic makes sure this doesn’t happen: 

We avoid creating a data warehouse – at least up front. We use smaller sets of data called data marts. We define them for each subject area. They’re focused, manageable, cost less time and money to build and are easily adaptable as your needs evolve. We prioritize the most valuable data sets, so you get insights faster. When you partner with eLogic, our team handles your project so your key players can be resourced for other priorities.  

Mistake #2: Wrong-Sizing Data Reporting Architecture  

We often see people make assumptions about the intended use of their data warehouse and select reporting tools based on those assumptions. They discover down the road that they locked themselves into a very expensive package and they don’t have the flexibility to adapt to new scenarios and requirements. In this situation, returns on the investment are more difficult to realize.  

How eLogic makes sure this doesn’t happen: 

We scale Microsoft Power BI with a cost-effective mindset. We usually start with a free version of Power BI and create a proof of concept with the data to prove out value and function. Power BI also offers the ability to model data within it; sometimes avoiding the need to first establish a traditional data mart. This can further reduce cost, complexity and time to deployment. We then work with you to determine if Power BI is the right tool for your initiative, and recommend a particular version (e.g. Professional, Premium) for your near-term and longer-term needs. We scale based on the value the insights warrant. 

Mistake #3 : Extreme Post-Implementation Support Requirements

We’ve seen countless firms set up massive data warehouses that are so large they can’t possibly be supported without dedicated teams and maintenance contracts. Customers then get locked into a contract to use outside support and end up sinking millions in day-to-day operations.  

The data also starts to age, things that are broken don’t get fixed and begin to deteriorate, ruining the validity of the data. One poor decision based on bad data will cause your users to become distrustful and less reliant on a major investment that ought to serve them better.  

How eLogic makes sure this doesn’t happen: 

Data marts are easier to support, and with eLogic’s hyper-care, we provide remote and on-site support, training, and thorough documentation. We also involve line of business subject matter experts throughout the entire project, so they are empowered with working knowledge and are independently capable to analyze business data without regularly involving IT.  

 

We establish a partnership with our customers. We create a consistent dialogue with the business users throughout the process, which informs and shapes the solution, to get to a highly polished finished product that economically realizes valuable business insights that lead to new revenue streams, process improvements, greater efficiency, and more.  

 


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