What is the ultimate goal of BI (business intelligence)? Some might use analytics simply to make sense of all the data they have, letting the available data dictate the analytics tools that are created. They take a whole bunch of data, push it into a BI tool, and see what happens. Simply visualizing data doesn’t always equate to business value, though.
Instead, the goal of business intelligence should be to solve business problems. Data analytics should be useful, actionable, and contribute business value. Developing BI from a value-driven approach can be achieved by bridging the gap between business and data science while relying on tried-and-true methods from the UX (user experience) design world.
How do you move from useless charts and graphs to powerful, informative insights? The key is learning what analytics insights are needed through a process called requirements gathering – it’s part of our proven dashboard design process.
Requirements gathering process in 7 steps
Before you can design or develop a business intelligence tool, you must complete the requirements gathering process. This involves collecting knowledge, information, goals, and challenges to understand what is necessary for an effective and impactful analytic dashboards or portal. Whether you are developing a single chart, a BI dashboard, or an analytics hub, begin with the process below.
Download a free Requirements Gathering Checklist:
1. Identify required participants
First, seek out a list of essential people whose input will determine the success of the project. Who are the end users, the executors, and the decision makers? Make a list of all participants and their roles. Each person contributes a unique perspective, so take note of their goals, willingness or reluctance to participate, and/or potential obstacles.
In most cases, people involved in requirements gathering should include:
• stakeholders leading the effort
• end users
• executives
• an IT manager
• a data scientist
• an analyst
• a BI developer
• a consultant
2. Start talking (but mostly listen)
Now that the stakeholders and end users have been identified, it is time to talk. This is the most essential step of the requirements gathering process, since it provides the information you need to move forward. You can talk in one-on-one, structured interviews, through group workshops, or both.
From stakeholders, you need to get a high-level perspective of business goals. What do they want from analytics?
From end users, you need perspective about how the right analytics will provide value and efficiency in day-to-day tasks. How can analytics help employees get their work done?
In all conversations, remember to extract information about current processes, challenges, and potential obstacles that might appear during development of an analytics tool.
3. Develop personas
After talking with stakeholders and users, you should consolidate that information into a few distinct user personas. A persona is a fictional character derived from real user information. It often represents a group of people in similar roles.
A stakeholder persona should focus on how analytics are valuable to the business, including top objectives and challenges to achieving those objectives.
An end user persona should focus on the challenges of navigating the existing system. The persona should also detail how analytics will improve day-to-day activities.
4. Identify persona questions
Using the goals and challenges you listed earlier, you can expand your personas by creating questions. What questions would your persona have that analytics can help answer? Clarifying these needs will ensure that your end product delivers value to your organization.
Just as each persona is unique, their questions are also unique. For example, a stakeholder for a HR analytics dashboard might ask how to reduce overall cost of attrition, while the HR end user might ask to see a chart detailing how many people they have onboarded. Different user personas have different objectives and perspectives when looking at the same data.
5. Scenario mapping
Scenario mapping is the process of discussing and then mapping, step-by-step, how each user persona question would be answered within a new BI dashboard. For example, could the user find answers through a KPI summary at the top of the dashboard, or will a certain type of chart be needed? What steps will the user take to find the information they need, and what actions will they take if they encounter a problem?
This exercise is a great way to verify that the new analytics insights will actually be discoverable, useful, and relevant. Because scenario mapping walks through a series of events in the shoes of the user personas, it forces you to focus on user experience design and consider the context in which your data will be used.
6. Group similar items
Next, determine what organization of information will serve the personas best. Group questions and associated tasks together by similar topics, themes, and personas. From these groupings, questions will begin to emerge about whether separate dashboards are needed for each persona, if topics can be separated by tabs, or if a blended view of charts and KPIs is the best approach. The process of grouping helps create a simple navigation flow during the design phase.
7. Check analytics data
In this final step, you’ll check whether your existing data can support your goals. Check each persona question against your current data and determine whether the data can reliably answer the questions. For end users to have confidence in your analytics, your data must be available, of good quality, and have sufficient velocity.
If there are questions that can’t be answered with current data, plan to answer those in later versions of your BI dashboard. As you near the end of this step, a realistic view of your first dashboard will begin to emerge. You can set goals for evolving data gathering in future versions. Use this opportunity to discuss with stakeholders whether they want to invest in data processes enough to answer unresolved questions in the future.
The seven steps of this requirements gathering process are essential for answering the question: What analytics are most important for the success of our users and our business?
Once that question is answered, design and development of a new BI dashboard can begin. Depending on timeline and budget, requirements gathering can involve several weeks of in-depth interviews and collaborative meetings with key players or it can happen over a few days. Either way, it is important to take the time to work through all seven steps thoroughly.
In analytics, it is not enough to just be data-driven—you must be value-driven first. Aligning analytics to user needs and business goals will deliver high ROI on business intelligence tools.
[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built="1" _builder_version="4.21.0" _module_preset="default" background_color="#3B55D4" background_image="https://logic2020.com/wp-content/uploads/2023/08/Slashes-for-Colored-Background.png" custom_padding="1px||1px||false|false" locked="off" global_colors_info="{}"][et_pb_row _builder_version="4.21.0" _module_preset="default" custom_padding="||0px||false|false" global_colors_info="{}"][et_pb_column type="4_4" _builder_version="4.21.0" _module_preset="default" global_colors_info="{}"][et_pb_text _builder_version="4.21.0" _module_preset="default" header_text_color="#FFFFFF" header_3_font="|700|||||||" header_3_text_color="#FFFFFF" global_colors_info="{}"]Like what you see?
[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row _builder_version="4.21.0" _module_preset="default" custom_padding="10px||30px||false|false" global_colors_info="{}"][et_pb_column type="4_4" _builder_version="4.21.0" _module_preset="default" global_colors_info="{}"][et_pb_button button_url="/connect" button_text="Connect" button_alignment="center" _builder_version="4.22.1" _module_preset="default" custom_button="on" button_text_color="#FFFFFF" custom_padding="5px|20px|5px|20px|false|false" global_colors_info="{}"][/et_pb_button][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built="1" _builder_version="4.22.0" _module_preset="default" global_colors_info="{}"][et_pb_row column_structure="1_4,3_4" _builder_version="4.22.0" _module_preset="default" global_colors_info="{}"][et_pb_column type="1_4" _builder_version="4.22.0" _module_preset="default" global_colors_info="{}"][et_pb_image src="https://logic2020.com/wp-content/uploads/headshots/Nick-Kelly.jpg" alt="Paul Lee" title_text="Nick-Kelly" _builder_version="4.22.1" _module_preset="default" width="75%" width_tablet="30%" width_phone="35%" width_last_edited="on|tablet" global_colors_info="{}"][/et_pb_image][/et_pb_column][et_pb_column type="3_4" _builder_version="4.22.0" _module_preset="default" horizontal_offset="-35px" horizontal_offset_tablet="0px" horizontal_offset_phone="0px" horizontal_offset_last_edited="on|tablet" global_colors_info="{}"][et_pb_text _builder_version="4.22.1" _module_preset="default" global_colors_info="{}"]Nick Kelly is the Director of Visual Analytics at Logic20/20. He is a hands-on leader in analytics with over 16 years of international experience in analytics and software development, deployment, adoption, and user experience.
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