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SmartData Collective > Analytics > Building an Ironclad Business Case for Business Intelligence
Analytics

Building an Ironclad Business Case for Business Intelligence

Eran Levy
Eran Levy
9 Min Read
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So you’ve decided you want to jump on the data analytics bandwagon and propel your company into the 21st century with better analytics, reporting and data visualization. But to get a business intelligence project rolling you usually need the entire organization, or at the very least the entire department, to get on board. Since embarking on a BI initiative requires will require an investment of time and resources – as well as a conceptual shift regarding the way the organization works with data – you might need to convince the relevant people in the company to take the leap.

Contents
1. Understand how much the current situation is costingRead more: Understanding the hidden costs of Business Intelligence2. It’s not just about data visualization3. Show how it solves current business problems4. Consider your data’s current and future complexity5. Relate to each stakeholder’s pain points6. Set actionable timeframes7. Show value before purchasing a solution

So you’ve decided you want to jump on the data analytics bandwagon and propel your company into the 21st century with better analytics, reporting and data visualization. But to get a business intelligence project rolling you usually need the entire organization, or at the very least the entire department, to get on board. Since embarking on a BI initiative requires will require an investment of time and resources – as well as a conceptual shift regarding the way the organization works with data – you might need to convince the relevant people in the company to take the leap. You’ll need to construct a solid business case that proves the value BI can bring to your organization. Here are 7 tips to help you make a convincing argument:

1. Understand how much the current situation is costing

The fact that you’re not currently paying for a BI solution doesn’t mean that the current situation doesn’t have its own costs: either due to IT resources being spent on tasks that could be automated with business intelligence, or due to lack of proper access to data and analytics. How many work hours are currently spent each week on generating reports? How much of a backlog is this creating for IT? How many times has your company failed to realize business benefits due to not being able to act on information in time? Do executives and mid-managers spend hours struggling with spreadsheet tools to understand their department’s performance? All of these are cost factors, even if they don’t appear as such in any budget report.

Read more: Understanding the hidden costs of Business Intelligence

2. It’s not just about data visualization

One of the first things you want to clarify is that the ultimate goal is not just to have nicer looking visualizations. After all, a chart is a chart, and more attractive graphics do not automatically translate into additional insight. For this reason, it’s critical to make clear that business intelligence is about more than just data visualization, and that the BI project – once launched – will actually enable the organization to find actual solutions to business problems, provide new ways of looking at data, reduce reporting time, increase data reliability and take some of the burden off the IT department’s shoulders.

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3. Show how it solves current business problems

Every company has its problems, and often data-driven methodologies can help solve these problems. Whether it’s high customer churn rates or ballooning operational costs, data analysis can help you understand where your business is stumbling as well as suggest possible causes and solutions. The ability to perform fast and accurate analysis of complex data is one of the main benefits of business intelligence: try to pinpoint 2 or 3 major issues and see how a data-driven approach could help tackle them.

4. Consider your data’s current and future complexity

It could be that currently your company is working with fairly simple data, and the types of analysis you’re performing are adequately addressed by solutions such as spreadsheets or data visualization tools. However, for growing companies this is unlikely to be the case for long — today even SMBs are finding themselves dealing with big or complex data, particularly in areas such as digital marketing, HR management and customer service. When your data does become more complex – e.g., will start growing in size to the point of “choking” the lightweight solutions in place, or you find yourself working with many disparate data sources – then there will be no choice but to transition to business intelligence software. However, waiting for a crisis to occur and then making decisions in “panic mode” is usually not the best practice, so if you have reason to believe the complexity of your data is going to grow in the foreseeable future – better to address that now.

5. Relate to each stakeholder’s pain points

Business intelligence tools can solve many different data-related issues in the organization, each of which affect different people: the CEO wants to see high-level reports of the organization’s performance across departments; mid-level executives want to use data in their day-to-day operations to make better decisions; IT professionals want to spend less time on maintaining, cleaning and integrating data for the business users to access; analysts want faster and more flexible analysis, etc. When making your business case, be sure to present a point that each relevant decision maker can sympathize with – clarify how this is a solution to their problem, as well as the company’s.

6. Set actionable timeframes

Implementing a BI solution is usually not a matter of minutes, but it shouldn’t take months either. People are naturally less inclined to undertake a huge project with no clear finish line, particularly one that will require time and money to be invested. Hence, you should start small, and set clear and near deadlines for stages such as requirements elicitation, defining KPIs and having the first dashboards up and running. With a modern BI solution, these timeframes should generally not exceed a period of days or weeks for a regular-sized implementation. If the decision makers receive a promise to see actual results in a short time period, they will feel more comfortable approving the project.

7. Show value before purchasing a solution

Finally – don’t ask anyone to divert budgets to this kind of project without first conducting a full proof of concept. Many BI tools also offer a free trial version, which you can use to evaluate to what extent the software in question provides self-service capabilities, and how it fits in with your company’s goals and current data situation. However – don’t settle for just a free trial period: insist on conducting an actual proof of concept, with the vendor you are evaluating, on your actual data and answering an actual business question. This can really be the clincher: the ability to produce a working BI system will be the absolute best way to showcase what business intelligence can do for your organization. Because after all – dashboards speak louder than words.

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