Data Analysis: Techniques & Tips For Strategy Reporting

At ClearPoint, we’re pretty gung ho about everything related to strategy reporting. But of all the stages of the strategy reporting process, data analysis is one of the most interesting. In this stage, you dig into the data you’ve collected and evaluate it in an effort to start drawing some conclusions. It’s also where you begin to build a narrative about past performance, and demand for data storytellers is rising.

In this article, we cover the essentials of analyzing performance data, including some common challenges around doing data analysis for strategy reporting, and a few data analysis techniques you can use to create compelling reports.

Data Analysis For Strategy Reporting

First, some context on where data analysis fits in the strategy reporting process.

Everyone wants an attractive, useful strategy report. The hard part is building it. We've broken report building into five steps and written about each one:

1. First you collect data from the variety of sources throughout your organization.
2. Then you synthesize the data. This means aggregating information, making appropriate charts, and presenting data in a helpful manner.
3. From there, you put qualitative analysis around the data, to glean insight into why measures are moving in different directions and how projects are impacting performance.
4. Then you build reports for the right audiences and distribute the information into the hands of decision makers who will react to the data.
5. The result is a great strategy report for your organization.

In the previous stage (synthesis), you organized and visualized the data. Now you work out the story it tells. That story will help leaders make informed decisions.

The purpose of the data analysis stage is to understand three things in relation to your organization’s performance:

• What happened in the past month (or quarter), i.e. did you meet targets or not?
• Why those things occurred
• Make predictions about what’s likely to happen in the future.

This is where the storytelling comes in. If you can’t communicate what your data says, the exercise is meaningless. Make sure all your data is accurate and up to date. If a number is off or an analysis is old, you’ll tell the wrong story.

Common Challenges Associated With Data Analysis

Many businesses collect large amounts of data but still miss the mark when they use data analysis for strategy. Only 32% of organizations realize tangible, measurable value from data. If your organization falls into that category, you’re probably running into one or more of these issues:

• The data interpreter is not the data owner. The people working directly on the initiatives, measures, and objectives are providing the data, but they aren’t always the ones interpreting it. That sometimes leads to misunderstandings or incomplete explanations about performance. For example, it’s one thing to know that 50% of your clients are in one sector, but another to realize that it represents only 25% of your revenue and that your marketing is focused on a faster and more profitable market segment.
• The data is not strategic. With today’s tracking technology, you can track almost anything you can imagine. But only a few data points matter for understanding performance. These are your KPIs. For strategy reporting, the challenge is to track these few key measures and put them in context with project performance and your goals. Providing analysis and insight on the key measures only is more valuable than tracking more measures.
• The data doesn’t tell the full story. Data is an essential part of storytelling. You can see revenue growth, supply chain challenges, market demand, and rising costs. But you still need analysis and insight to connect the pieces and interpret them correctly. The pieces of the puzzle may point to a great opportunity, or they may warn that you need to change your organization dramatically to prepare for a future of challenges.

You can address these issues and manage your data proactively. It isn’t as hard as you think. You don’t necessarily need an entire department dedicated to data analysis or an army of statisticians. What you do need is a solid reporting strategy in place and software to support it.

We’ll cover the benefits of software in a minute. First, here are some common methods for analyzing data.

Data Analysis Techniques

When you analyze performance, evaluate all data in the context of your goals. Start from your organization’s overall objectives and look at what the data suggests about your likelihood of achieving them.

Here are a few ways to analyze your data and give your audience the information it needs for decision-making:

• Do a descriptive analysis of performance. Start with some of the basic questions of journalism: what happened and when did it occur? Use both hard numbers and narrative to paint a complete picture. Consider using line and bar charts to compare values, or pie charts to show numerical proportions.

• Do an explanatory analysis. Determine why it happened. Sales may have gone down because key team members left. You may be struggling to keep up with demand because of supply chain problems. Your site may have gotten less traffic this quarter because of a change in Google’s algorithm, or because of the way your site was recently reorganized. Understanding why something happened may require digging into supporting metrics, or exploring relationships between data sets.
• Do a predictive analysis. Consider what is likely to happen in the future. Use the results from the previous analyses to see where performance might be headed if things keep going as they are. Trendlines can be helpful for visualizing data over time.

TIP: One strategy that helps reveal data relationships is to analyze groups of similar information together. For example, a list that includes all financial metrics that are red (off target) would show you that both net income and expenses are off target. This makes it easy to see that expenses are causing the drop in net income, rather than a lack of sales.

How To Simplify Data Analysis

Whatever data analysis methodology you use, it’s worth investing in a software tool that will make it easier. Data analysis happens on a regular basis, ideally once a month or once a quarter, but it shouldn’t take all your time.

A lot of organizations attempt to use tools like Word, Excel, email, Slack, and Teams to gather analysis from their teammates. This doesn’t last long. Multiple tools lead to disorganization and inaccurate data. Other organizations use special analytics tools that are good at slicing and dicing big data, but fall short in the area of strategy reporting and data management. All of these tools are fine when used individually, but they won’t work if you’re looking for something to help you manage the entire strategy reporting process, including data analysis.

‍ClearPoint is strategy reporting software that helps manage and track your strategic plan to increase the likelihood your organization reaches its goals. For ClearPoint users, data analysis is easier because our software:

• Shows linkages between projects (initiatives) and objectives to keep strategy at the center of your story

• Enables users to drill down into supporting metrics to understand performance
• Displays qualitative analysis alongside quantitative data to provide additional context
• Automatically creates the necessary charts and other visuals to support a detailed analysis
• Houses all your strategy data in one location for simplicity and accuracy, so you no longer gather data across multiple tools

The real value of ClearPoint is how much time it saves on strategy reporting, and how easy it is to use. We’ve automated a lot of the processes around data analysis, like automatic reminders for users to update their data, so you don’t have to manage the small things. You can focus on using your data to hit your goals and KPIs.