Updated July 29, 2020
Whether you are just starting an analytics program, or feel a bit dead-in-the-water with your analytics efforts, this 3 step process is for management teams looking to strategically set-up reporting and data visualization.
Here’s a scenario:
You have successfully implemented a data pipeline solution at your business, including a top-notch data visualization tool to bring your business data to life. You have invested time, resources, and money in a business analytics program at your organization and are ready to reap the rewards of being a data-driven business.
But where do you start? How do you learn this new technology and start using it effectively at the same time? What reports and dashboards should you pay attention to? Are there any standard reports that work for your business, or will you have to build them all from scratch?
You want to see a return on your investment in this new technology, but there is so much data, so many ways to view it, and so much to learn…
We have seen this situation play out many times. Smaller businesses feel this pain worst of all because they may not have a dedicated role for managing and analyzing business data.
It is one thing to understand the strategic value that business data can provide, and a wholly other monster to efficiently visualize and analyze it.
This often leads to trepidation when considering an investment in business analytics, and rightfully so. After all, what use is a new technology if it is difficult to learn and a struggle to implement into daily use?
We are going to address this problem head-on and provide our practical recommendations for using your new analytics technology.
How to set-up reporting and data visualizations strategically
If you have read other posts from our Foundations Series, then this will be a well-established point: intentionality with business analytics is vital for success. Our goal is to illustrate a repeatable process that will enable any business, especially smaller businesses, to find value quickly and long-term success with analytics.
Step 1: Identify high value goals
Strategize with your team to identify existing business goals. This is a great opportunity to introduce data culture practices at your business. Schedule a few half day sessions to white-board ideas, perhaps start with leadership and then include all team members.
Goals may be broad or specific, here are a few examples:
Increase sales by 15% every quarter
Reduce time to close customer support tickets
Reach 1,000 followers on LinkedIn
Track operational costs by department
The purpose of this exercise is to build a comprehensive “master list” of all existing goals within the business. The list does not need to be exhaustive, only a starting point. It will become a road map for strategic reports and visualizations.
Keys to Success:
Don’t re-invent the wheel. Use goals that already exist within the business, whether company-wide strategic goals, department-based, or role-based.
Get a healthy assortment of short- and long-term goals, as well as, goals from a variety of departments.
Don’t get bogged down in figuring out how to measure a goal, any business goal should be included.
Rank each goal by expected business value once the list is complete. We recommend a simple scale of 1-3 with 1 being most valuable.
Step 2: Define metrics and success criteria
Now that we’ve built and ranked a list of strategic goals, it is time to turn each goal into a useful report or visualization for tracking progress and analysis. This exercise will require creative problem solving about how to best use business data.
Using the business value ranking, choose a selection of ~5 goals with high expected business value. Include goals from various departments and time frames (short-term and long-term) to create a breadth of understanding and ease the learning curve.
Next, define how you will measure progress and success for each goal. To start, draft a brief abstract that details what the goal is, how it will be measured, the time frame to achieve the goal, and what is considered success.
At this point we always recommend management teams working with a data analyst to get their reports and visualizations implemented. Leave the strategy to management, and technical implementation to data experts.
Technical information to provide a data analyst
(If you are wondering who this data analyst is, check out our post on building a data team).
How will you measure progress and success: what business data aligns with this goal?
Does this goal use data from a selection of fields and/or objects within your business systems? Provide specific field and object names and the systems they reside.
How do you prefer to have the data measured and/or displayed?
Time: Monthly, Quarterly, Annually
Currency: Rounded, 2 Decimal Points
Quantities: 10s, 100s, 1000s
What is the success criteria? Should there be a goal line?
Are there notifications that should be implemented for if/when a value reaches a certain threshold?
Is there a specific visualization you prefer for viewing this data?
Who should have access to this data?
It is important to be as specific as possible, the end-result will be a clear description with enough technical information for a data analyst to take a first pass at implementation.
Keys to success:
Create a data map of your business data to know what facets of your business you are currently tracking and how your data flows through your business. This will ease your efforts when defining your goals, and provide important context for the data analyst.
Collaborate with a data analyst right away, ideally they would have helped with the implementation of your technology. Data analysts can help evaluate what your systems currently have and provide recommendations for more advanced and complex data visualizations.
Test out different types of visualization for the same data. Establish what works best for your business and users.
Remember that one goal may require more than one report to measure it effectively and may benefit from its own dashboard.
Step 3: Implement strategic reports and dashboards iteratively
At ReconInsight, we take an iterative development approach when working with our clients on strategic reporting. In the context of setting up reports and dashboards, one iteration includes: identifying, defining, and the implementation itself. In our experience, each iteration generally takes 2 weeks to complete when you factor in back and forth between the business and data analyst. It is enough time for the business to be deliberate and strategic with their requests, and still see substantial forward momentum.
Check out an interview with Chris and Kevin, Iterative Business Analytics: Interview with the Experts.
Up until now, the ‘identifying’ and ‘defining’ efforts can be accomplished largely within the business, no outside help necessary. As we mentioned at the start of this post, the technical implementation of reports and dashboards can be a daunting task for users that have no prior experience with data visualization technology. For this reason, our methodology is built around the expectation that a data analyst will be used to initially set-up your reports and dashboards.
Out-sourcing technical services to a skilled data analyst will ease the burden of needing to learn a new technology right away, and allow you to focus on the strategic use of analytics tech.
Keys to success:
Set deadlines for all team members, to guarantee speedy implementation and fast turn around of additional requests from the business to the data analyst.
Allocate time for the project in team members’ schedules.
Each iteration should include defining ~5 additional goals and implementing corresponding reports and dashboards.
Continue to collaborate with the data analyst and be inquisitive about how the technology is used.
Establish Standard Operating Procedures for reports and dashboards.
Implement a naming convention and organization structure.
Keep a directory of which reports/dashboards align with which goal.
Assign ownership of specific goals and their corresponding reports to the appropriate team member.
Create a process for how often reports and dashboards should be reviewed and progress tracked.
Final Thoughts
“The learning curve for analytics software and strategies is steep and unwieldy if left to chance.”
It is important to approach strategic use of data with intention. The learning curve for analytics software and strategies is steep and unwieldy if left to chance.
Every business is unique in how it operates and that is reflected in how data is used. While we may not have provided a succinct listing of ‘dashboards and reports you should use when starting business analytics’, the methodology we have presented is what we encourage all of our customers to use.
It is also important to note, this methodology relies on three things: intention, a skilled data analyst, and a strong data pipeline. These important, foundational investments are vital to creating a valuable, efficient business analytics program.
Ri360’s included data analyst services
In case you didn’t know: ReconInsight’s business analytics software, Ri360, includes data analyst services in our monthly subscription costs. We built our monthly subscriptions to include services to ensure that our customers continue to see value and testing the limits of analytics with Ri360.
We also provide project-based and ongoing support data analytics services, as needed.
