There are many different ways to go about introducing Power BI as the business intelligence tool for an organization. The tips below outline key considerations from a non-technical perspective. They will give you a few things to think about in advance and hopefully will help you succeed in your organization.

10) Have a data analytics strategy and get buy-in from executives

We can all agree that data and analytics can be complicated but the insights are powerful, and organizations can’t afford to ignore them. Leaders expect to make long-term decisions that can be backed up.

The right data analytics strategy connects the organization’s vision with a value proposition. The first step is to have a clear understanding of the organization’s mission. Second, prioritize business outcomes that matter the most, while focusing on delivering business goals. Define what type of need the organization has now, and what it will need in the future. For example, is the organization ready now to enable D&A as a generic capability, focusing more on operational reporting needs? Or is the organization ready to make D&A the driver to achieve new business goals? Use actual examples from the past to explain operational inefficiencies or a decision that was made that had a negative impact. Once you get clear goals and the value Power BI brings to the organization, it’ll be much easier to get the buy-in of executives and stakeholders.

9) Have a clear and well-define scope (but be flexible!)

This one is tough. But Let’s start by saying the scope should be defined by the business’ needs jointly with its IT partners. As the author Kimball puts it: a business intelligence project scope should be meaningful, yet manageable. Meaningful translates into perceived business value. Manageable means doable. With that, consider starting small.

Often times, projects start with the scope well-defined, a project plan is in place with a detailed timeline and the inevitable happens: things change. While it is critical to have a clear path and well-define scope from the beginning, it is also just as important to be able to adapt when things come up. While every risk should be assessed during a discovery phase of the project, sometimes, only when the work starts is when the skeletons come out of the closet. Be ready to make changes to the scope and plan as things continue to evolve. Lastly, know that what is NOT in scope is just as important as what is in scope. Communicating what is not in scope will set clear expectations to stakeholders.

8) Focus on data governance from the very beginning

This is a big topic. A good data governance strategy ensures data usability, availability, privacy, and security. Don’t wait until the end of the Power BI implementation effort to define a data governance policy. There are many ways to structure a data governance policy. Some things to consider are having data stewards or a governance board, these are people who help set standards and enforce them. Data is a business asset, therefore, business users should be involved when defining data standards. Establishing master data management principles will drive and enforce data quality. Lastly, governance policies help the organization achieve data maturity goals and it continues to grow into a strong data-driven culture.

7) Execute a solid communication plan

The value of keeping the project sponsor and stakeholders informed at all times cannot be undervalued. Proactive communication is done in a number of different ways. Start with a kickoff meeting and explain things like roles and responsibilities, the project background, what is and isn’t in scope, the constrains, issues and risks you know right off the gate, and the priorities will level set all involved. Make sure you keep them informed by consistently sending out a standardized weekly status communication to let them know of the progress and current issues. Hold project review meetings with the same group (perhaps monthly or at the end of major milestones) to ensure they know where the project stands.

6) Have a solid implementation team or an implementation partner you trust

It may go without saying, but implementing a new business intelligence solution is no small feat. So make sure the organization’s IT team has the capabilities and, most importantly, the capacity to take this on. Start with an experienced project manager and a project sponsor. The core project team should include a data architect, business analysts, data stewards, data scientists, a database administrator and a compliance and security lead. It is critical to have the right talent with the capacity to execute the project under the project manager’s leadership. If your organization doesn’t have the capacity to dedicate a team, consider contracting with a implementation vendor to do the job. But finding the right one is a task all in itself. Make sure the vendor you consider has the right industry experience, the ideal skillset, a solid track record and one who puts the customer first. Once you can narrow down your vendor options to 2 or 3, perhaps ask if you can have a “recommendation call” with a past or existing client.

5) Have an implementation roadmap

Regardless of which project management methodology you choose, whether it’s agile, waterfall, or something else, it is best to communicate when various milestones, deliverables and tasks of the project will be completed. You can imagine there are many phases and steps to implement Power BI at any organization. A project roadmap should contain the why, what, who, when, and how the implementation will happen. A roadmap is the chronological view of the milestones and deliverables. While it can be pretty high-level, it provides transparency, which will be appreciated by stakeholders. We all heard the saying “change is the only constant”. A roadmap should be flexible and change should be expected as you go through the steps to bring Power BI to your organization. The point is that anyone can look at it and know what’s been done and what’s coming up next. You can find thousands of roadmap templates online. Besides being an effective communication tool, it also enables to adapt due to changing requirements. Regardless of which tool you choose to use, make sure to have an easy-to-read format with the appropriate level of detail to your audience.

4) Consider what needs to happen after the implementation

So you have a brand new shiny business intelligence tool deployed to production. Users have all the access they need. Then what? Is the IT team able to maintain the Power BI solution? Can they continue to develop it as needs evolve? Do users know how to use the tool? Will they need training? Are there resources available both to end-users and to the IT team? Consider that Power BI has frequent releases. How are these being rolled out to end users? If the organization’s existing IT team can’t take on all responsibilities on day 1, then consider contracting with a vendor who has the specialized service to support Power BI and users in your organization.

3) Make a realistic readiness assessment

If your organization is not ready yet to adopt a new business intelligence solution, I suggest you slow down or put the plans on hold. It is far better to pull the plug before a significant investment is made than move forward with an implementation filled with risks, resistance, and obstacles. That is a recipe to fail. There are several indicators, but one of the most important indicators of readiness is whether the organization has the support of at least one strong sponsor. This sponsor should be an influential leader with a vision for the positive impact a new solution brings. Another indicator is the general understanding within the organization there is great need to move towards a data-driven culture, preferably, with a sense of urgency for improved access to information. The more you can get the business behind the project, the more likely it’ll be successful.

2) Consider the best project management methodology for your organization

Deploying a new business intelligence solution like power BI is no small feat. Some project managers will argue there is the ONE way of going about it. I will say, the best way, is your way (wink). To start, select a competent project manager who can handle the tall task. A strong project manager has the ability to identify, react to, and resolve issues before they escalate into serious risks. For technology product-type implementations, the Agile frameworks have proven very effective. Whether the project manager is a strict scrum master or Kanban believer, having an iterative delivery in short timeframes in an incremental manner, while keeping the focus on the business requirements will usually lead to success. The main purpose is to deliver business value. Collaboration between developers and stakeholders cannot be undermined, and creating a close partnership with the business is absolutely critical.

1) Know the end users and their requirements well

If you’re on the path to deploy Power BI in your organization, at some point you’ll need to understand what the requirements are from the business, as well as IT. Requirements should be a progressive elaboration exercise. It should be expected that requirements will change over time, specialize as you analyze what you know so far and start developing. There are many techniques to collect and analyze requirements. There are discovery workshops, interviews, process models and more. A strong facilitator, sometimes the project manager, will encourage both the business and technical delivery teams to come together and deliver value while meeting the organizational needs. In today’s technology environment, where transformation, ambiguity, and complexity are the norm, requirements gathering and analysis work are critical to success.

I hope these tips help you successfully deploy Power BI in your organization! Find more business intelligence information here.