4 Best Practices to Follow When Selecting & Implementing Your BI Tools

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Selecting and implementing a BI tool is no trivial task. It takes time to get the approval necessary, and sometimes it feels like you have to jump through more hoops than a circus lion. It’s true that having across-the-board buy-in is essential, but there are ways to assure that your BI implementation doesn’t end with a crash and burn, like so many other enterprises have faced. Here are the best practices to help your entire organization get the absolute most out of the BI tool you choose.

1. Be Sure the BI Tool Matches the Needs of Executives, Operations & Production

There are three areas where a BI tool tends to meet resistance: the boardroom, operations, and the production floor. If you want a tool that will be leveraged fully, embraced company-wide, and thereby delivers a solid ROI, get buy-in from these three areas. Achieving buy-in is more than taking on an executive sponsor. It means building a solid relationship with these people and learning exactly what it is they need out of a BI tool. Will it deliver the analytical answers they most need? Will it do so quickly and efficiently? What do they demand out of a user interface and user experience? You don’t get these insights from a 1-hour brainstorming meeting. It comes from taking the time to get to know these people, how they do their jobs, what the pain points are, and what their goals are.

2. Be Sure IT is Comfortable with a Self-Service Tool

A few years ago, tech departments were still resistant to the concept of self-service business tools. That is changing. IT has readily embraced BI solutions, partly because tech departments (like most departments) are increasingly charged with doing more for less. Instead of viewing self-serve BI as sidestepping them, tech departments are glad for what the business side can do without lots of extra work on IT’s part.

It also helps that these tools provide a high level of data security, are relatively lean in terms of network and systems resources, and the data can be collected and integrated into other analytical systems for a fuller view of the enterprise’s data ecosystem. The shift in attitude can be attributed in no small part to the acceptance and even embracing of the borderless enterprise.

3. Institute Good Governance for Both Data & BI

A solid BI solution begins before the new tool is even implemented. It entails a good data governance policy. Data cleansing is essential before feeding it into your BI tool, because good analytics is useless when performed on bad data. But a governance policy goes beyond mere data cleansing. It also involves securing the data. What levels of encryption do you use for data at rest? What are your access policies and procedures? What are the consequences for failing to adhere to policy? All of these things go into a solid data governance program, and upon that you can build a strong governance policy for your BI tool.

4. Choose a Product That is Flexible & Scalable

Another common roadblock to adopting a great BI solution is that businesses fail to foresee their needs into the future. You don’t want your tool to become cumbersome or obsolete when you open a branch office in a new country, or roll out a product line that’s different from what you’ve always done. The BI tool must be adaptable so that whatever the future holds for your business, the tool can adapt and manage. That means choosing a BI tool that is both flexible and scalable.

The selection process goes better if you have a tried and true format for selecting mission-critical enterprise software. Take advantage of our free software selection requirements template.

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SelectHub4 Best Practices to Follow When Selecting & Implementing Your BI Tools

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