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5 Common Problems with Enterprise Reporting

To get ahead in your industry, you need an agile business that can react quickly. Key decision-makers need business insights delivered to them efficiently and effectively. Companies usually achieve this via enterprise reporting and cooperation between business and data analysts and decision-makers

However, if these reports don’t provide adequate context and reasoning, it can lead to severe problems. People may dismiss valuable information as irrelevant, built from bad sources, or not offering any real value to the organization. At its’ worse, bad reporting can make people begin to question the integrity of the organization’s data as a whole.

Here are some common problems to avoid when building an enterprise reporting strategy.

#1 Not having a coherent reporting strategy

Companies have their data spread through several sources, locations, and ERPs. With all this variety, having a well-defined reporting strategy is the only way to keep information consistent, especially if the technology used for each source also differs. Despite that, some companies will still rely on a “play it by ear” approach, creating reports on-demand with the tools they have available, like dashboards.

Without a strategy, your organization's reports will be a chaotic free-for-all where data users can submit whatever they like. Beyond the disorganization, it gives your users and report generators more information to comb through (with no clear idea of what is relevant, what has been included in previous reports, what's the structure and convention, and no easy navigation through the report), lengthening the entire process.

The result of an incoherent reporting strategy is:

  • Users cannot find the answers they need in a mass of empirical reports.
  • Communications slow down or even stop.
  • Reports take longer to build and become harder to repeat.
  • People mistrust reports or do not know which ones contain the most up-to-date information.
  • Reports are hard or impossible to compare with each other.
  • Missing integrity in reporting, with each chart showing the same data differently.
  • People coming to different conclusions from the same report.
  • People miss the big picture or most crucial point of the report.

The first and foremost step to enterprise reporting is having a coherent and repeatable reporting strategy. Your strategy should contain protocols like:

  • Data Formatting and KPIs. Having a standard definition of data across the enterprise while keeping track of key performance indicators (what you need to report on) will keep all of your reports relevant and uniform.
  • Standard data glossary and understanding. Having a shared understanding of what data and terms mean helps bridge the differences in perspective on the same data from different people
  • System and tools. Your tools should be self-service for employees to create near-real-time data visualizations and snapshots from their data sources. Having one that automates this process will help standardize formatting and other stylistic elements.
  • People and organization. Prioritize reports that link source data to the goals of the company. Then identify the best individuals to create those reports.
  • Reporting governance. Manage reporting and data access by defining rules and responsibilities of various data users for standard reporting, raw data, etc.
  • Report catalog: Metadata management for tracking reports. I.e., making sure people don’t create the same reports twice.

#2 Not having defined reporting templates.

Creating a template is one of the best ways to standardize your reporting. Since data sources are diverse, users often work with data in a different “shape” (held in tables with different names, labels, columns, and structures) or other variables like coding schemes, product names, and currencies.

Below you'll see an example of how charts can change because of no standardized rules. The first is in Dollars with a pointed curve, while the other is in Yen with a smoothed curve. As you can see, this makes the charts much harder to compare, even though they are displaying the same data. If your company uses Dollars as its primary currency, then all enterprise reporting should be in Dollars as well.

Users won’t know which final format it needs to be in to make it consumable and comparable with the rest of the organization (no universal reporting structure, labeling, currency, etc.). At its worst, this variation can result in entirely different conclusions from the same source data.

Setting up a universal standard template (including colors, headers, footers, chart types, data formats, etc.) will ensure reports are in the same style. This will make your reports:

  • Look more professional.
  • Give all users a clear idea of what information their report should contain and how it should look.
  • Easier to compare and interpret.
  • Avoid putting the enormous responsibility of reformatting every report on one design team.

#3 Relying only on dashboards for enterprise reporting


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If a company doesn’t have a coherent reporting strategy, maybe it’s because they usually build most of their reports from the company BI dashboards. A BI dashboard is a data visualization that gives an at-a-glance summary of key performance metrics.

Dashboards are excellent at monitoring a business but aren’t excellent at reporting on it. This means that they are good at alerting people of problems and following metrics on a day-to-day basis but not great at creating detailed findings for further analysis and communication.

Dashboards have problems with context: explanation and narrative

Dashboards miss the context of their reporting, providing only raw numbers with no narrative. Even if you wanted to use one for a formal report, you would have to constantly click back and forth between widgets (or screenshot the relevant ones), manually do all the drill-downs, and verbally explain your narrative or the connections between the data.

There is no space to add textual explanations or an ability to reveal information gradually. The data user or reporter would have to guide people unfamiliar with the dashboard almost by hand to get them to the necessary takeaways and insights.

Dashboards can lead to analysis fatigue

Users will experience analysis fatigue as they look at the same thing daily, hoping for some small change. This could lead to them missing an important data point when it finally arises (because they expect it to stay the same). Human bias can also get in the way as they won’t have time to analyze every point individually. They will automatically favor those they expect to change, ignoring elements they expect to remain stagnant.

How to use dashboards for enterprise reporting

Instead of using them as your only source for reporting, you should use them for their intended purpose: operational monitoring of the business. Dashboards are a great source when looking for sudden changes in KPIs, keeping users on the same page, and knowing what topics to include in your report (if it’s on the dashboard, then stakeholders are probably interested in it). We recommend using dashboards as one resource for your reporting, not the only one.

#4 Slide decks require a lot of copy & pasting and aren’t easy to design

Because dashboards are limited, you will need another tool to create reports that tell a story. This is where most companies turn to presentation software like PowerPoint or Google Slides. These tools allow you to present enterprise reports on a slide-by-slide basis with the ability to add textual explanations, graphics, and annotations.

However, while these tools are excellent for unveiling information gradually, using them for enterprise reporting is often inefficient. Let’s take a closer look.

Too much copy & pasting and switching between tools

These tools can be time-consuming because they don’t connect directly to your data sources. You will have to upload the source data into a chart or visualization creator (or take manual screenshots of the dashboard), leading to a lot of copy and pasting and clicking back and forth between tools. There’s more possibility for human error (missing a data point, adding the same datapoint twice) during this transfer of information from one tool to another.

Slide decks don’t update automatically. Every month (or however often these reports are due), you will have to recopy and repaste all the new information back into your slide deck. This is why consistent slide decks take so long to recreate, even with a template.

Not everyone is a graphic designer

Presentation tools like PowerPoint and Google Slides put a lot of responsibility on the user to design them. Most enterprise reporters aren’t graphic designers and, without a decent template, will have to rely on the most basic visuals for displaying their information.

The alternative is to put a massive amount of work on a design team to make every report visually consistent. If these slides look unprofessional, it can have a detrimental impact on the audience’s opinion of the report and the information it contains.

#5 Reports aren’t designed for independent consumption

Many organizations make the mistake of thinking a report presented with a narrator can be just as easily understood without one. Once the report has been delivered, a version with the narrator’s notes or annotations is usually uploaded onto the cloud. They expect all users to catch themselves up from there.

However, reports presented by a narrator will typically not display all of the relevant information, allowing some space for the narrator to fill in the gaps and connect the dots. Unless the annotations perfectly capture the narrator’s mind, at least some information will likely get lost or miscommunicated along the way.

Below you'll see an example of how hard it is to interpret a graph without any narrator or additional explanation

You should keep this in mind for your enterprise reporting because it will always have to be consumed independently at some point. Every interested party or stakeholder can’t be at every meeting. People often want to look back at presentations as a resource or compare them with a more recent version. When they do, you don’t want them to be confused or miss a critical insight.

Reports lack textual explanations

Text explainers that link the visuals and guide the audience through the narrative are imperative. This will help the audience can move through the information at their own pace without missing the main point or failing to connect the dots.

Tips for creating narrator-less reports

If you'd like to learn more about storytelling with data, you can read our article here. By keeping in mind that audiences will be consuming your reports independently, you can add features and elements which allow users to understand them better:

  • Interactive drill-downs for viewers to extract exact values from charts
  • Add links to particular data sets for people who want to look at the source data.
  • Add textual explainers between charts to reference how they are connected and drive the narrative forward (data stories can generate these automatically with AI).
  • Highlight significant changes with different colors or symbols, providing a legend next to the chart to explain their meaning.
  • Use the title of your charts to emphasize their main conclusion or takeaway (instead of just naming them after the variables they’re depicting)
  • Present information in an organized and particular order that moves chronologically through your narrative: Thesis > Evidence > Conclusion (not just individually isolated charts with lots of notes under them).

Simplify your reporting workflow

If you’d like a tool that helps you avoid all these problems, try Data Stories at datastories.ataccama.com. It connects to your sources, has a wide assortment of visual options and customizable animation, and presents all your information in context-rich explained narratives. It also offers AI insights to help you tell your story and has an easy and secure publishing option for sharing with your preference.

Start telling stories with data today

Ataccama Data Stories are free.
10 public stories • 10 datasets • 10 million data rows

Start telling data stories

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