Why Does Your Reporting Suite Become Unreliable Over Time
- March 27, 2024
- Posted by: FOYI
- Category: Blog
At the very beginning of news on television, it was mostly a way to report what was happening. However, news evolved into analysis, documentaries, opinion and these days its a lot more.
Along similar lines, when data reporting started out, it was about columns and rows of data. It was about the sales figures yesterday or the profit for the past financial year. Over the years, this started to evolve into charts, comparative charts, benchmarks and these days, its a lot more.
The ease of use and quite frankly, the free tools such as Power BI got just about anyone who wants a report to build a report. While this sounds like a new solution to businesses, it creates reliability problems in the future or rather the lack of.
While the exact problems they create are different across multiple industries, the signs of an unreliable reporting suite in the making are very similar.
Signs Of An Unreliable Reporting Suite
As data is more accessible to people within your business, everyone has a report and it has their own data. For example, if your sales team define customer as a contact person in the customer account Vs your finance team defining customer as the business itself will create huge differences in the new sales and cost of acquisition metrics.
Multiple versions of the truth is by far the most common and the most destructive sign of unreliable reporting.
The underlying data that is used to building the report is often not organized. For example, sales data used by your sales team does not match with the data as per your marketing team. In most cases, this has less to do with the reporting but rather the way the underlying systems operate. May be the marketing data is received from third party retargeting vendors that has problems.
To make things worse, sometimes, a part of the data is available in the organized data warehouse while the rest is available in a production system that is not very “organized”. Organized data is the first milestone in generating profits by harnessing your data.
Some new report requests take months to be complete. This is equally true for businesses with a very nicely organized data. This is how the story generally goes.
1. The reporting analyst works with the person who made the report request and sources the requirements.
2. As the report starts getting built, new people get added to the list of subscribers of the report.
3. As the number of subscribers increase, there will be small changes to the original requirements to the report.
4. These small changes will entail some change to the work done so far. As the rework is done, more changes come by and this makes the report build an eternal process.
5. The original requestor of the report gets upset that a simple report cannot be generated by the IT team.
The above reasons result in a constant back and forth between reporting analysts and the business teams. This leads to the businesses losing trust in the reporting analysts and the business stakeholders begin to question the technical credibility of the reporting team.
On account of the frequent change in the scope of work of the report requested, the reporting analyst looses trust in the business team. The reporting team begins to doubt if the business teams really know what they want.
As both the reporting and business teams lose trust in each other and the meetings turn to debates, the IT leadership gets involved.
The IT leadership starts to ask for a more regular update on the day to day progress and concludes that the key problem is expectation management and that happens to be the job of project management team.
This starts a back and forth discussion between the IT leadership and the project management team and generally results in the IT leadership questioning the credibility of the project management team.
On account of all of the above situations, the people involved sometimes leave the job or are asked to leave. The new joinee is expected to finally make things better. However, it remains the same for the most part.
What are the key reasons for an unreliable reporting suite?
Let us begin by understanding what we at FOYI mean by reliable. Simply put, a report or a suite of reports is considered reliable when you know exactly which parts of them are accurate and which of them are not.
As for the parts that are not accurate, as long as you know how incorrect the data is (e.g. 3% to 7% off ), we would still call the overall report as reliable. The report is reliable in the sense that you can rely on it to make informed decisions i.e. knowing its strengths and limitations to the fullest degree.
There could be multiple reasons for unreliable reports. Here are the major ones that we observed in our projects.
No prizes for guessing the major cause of unreliable reporting is data quality. There is no need to explain this any further.
Reports need to be for a specific audience. Often times, we notice that a report has multiple audience types from head of the department to the grassroot level staff. While this may seem logical, it creates a whole lot of maintenance issues and scope related issues over its lifetime.
For example, the head of marketing is focused on the overall efficiency of the marketing budget at a month-over-month level across all channels while the marketer working on social media ads focuses on the campaign effectiveness at a week-over-week level. Each of the data points will involve different rates of refreshing the report and the month over month values will not match the sum of the week over week values over a month.
Remember, a week extends between 2 months and that causes confusion.
If there are multiple audience types, the purpose will also tend to be broad and therefore the report will inadvertently be spread too thin across multiple purposes.
The purpose needs to be very clear and as precise as possible. For example, if you are in a logistics business with a fleet of 500 trucks and you have a monthly utilization report for the yard manager, the purpose could be as follows
Measure the number of hours a truck is utilized as a percentage of hours it is available to be used.
The purpose is specific enough to understand that if the truck is off the road for repair and maintenance, you are not considering that as part of utilization as it is off your yard and the yard managers (let us assume) are not responsible for that truck until the truck is ready to be used.
Continuing the example from the purpose of the report above, the yard manager can act on the report by either trying to allocate the available truck to a job or have an explanation ready for the management as why it is not utilized.
Many times, the outcome is not clear and therefore, the reports do not get used much.
At FOYI, we build reports and dashboards for all audiences and purposes. We will help you to get your reporting suite back to reliability. Check out our services page for our visualization services.