You’ve probably heard of big data, the information that large corporations collect on worldwide users. On a smaller scale, companies of all sizes use data to gain valuable insight into their operations, industries, and customer bases.
Modern businesses depend more on data analytics and reporting to better understand the environments in which they operate and the effects of their actions and competitors’ actions. Data can help businesses predict future turns of events and potential consequences of big and small decisions.
Keep reading to understand how analytics vs reporting differ and how the two can help your business make smarter choices.
The Definition of Analytics and Reporting in Business
Analytics and reporting work hand in hand, but they aren’t one and the same. Reporting answers the “what is” questions, and analytics addresses “what does this mean?” If reporting is a trial, analytics would be the jury’s verdict. It’s important not to treat reporting and analytics as indistinguishable items. The two serve different purposes that must be kept separate. Let’s take a look at how the two differ.
What is Analytics?
Analytics allows us to draw conclusions based on factual data. This involves questioning why things happen, what causes them, and what can be done about them. Analysts use data reporting to discover business insights and use them to make informed decisions.
They take facts, apply expertise and knowledge, and draw conclusions. In order to perform quality analytics, reporting needs to be straightforward and digestible so that viewers can understand the facts.
What Is Reporting?
Reporting is the organization and representation of data in a clear and navigable way. It involves collecting data from various sources and formats and creating data models like charts and graphs. From there, businesses analyze reports and use them to make smarter, more strategic decisions. Reporting focuses on what is happening; analysis takes it a step further to figure out why.
The Importance of Analytics & Reporting
Analytics and reporting are essential for the success of any business, no matter their industry or scale. Companies that recognize and utilize the strength of data are able to get a leg up on their competitors — knowledge is power. Reporting and analytics are significant in the following ways:
- They allow us to view data in a digestible way.
- They help us to understand our business environment better.
- They make it possible to analyze facts and improve decision-making.
- Actions will be more calculated, strategic, and informed.
- Management can use reporting and analytics to keep lower-level employees in the loop.
Why You Should Utilize Both
You may still think that reports and analytics can be lumped together. Think about it this way. Raw data is essentially indiscernible information. You could have thousands of pages of numbers in the form of Excel spreadsheets or CSV files to read through and still not get anything out of it.
Dynamic reporting puts raw data into a usable, meaningful format. Analytics takes the facts and applies them to real-world scenarios. It goes one step further by taking data models and pointing out trends and meaningful patterns.
What Is the Difference Between Reporting and Analytics?
We will differentiate reporting vs. analytics by defining the goals of each and demonstrating how they differ. As it becomes more clear, we’ll explain indicators that can be used to tell the two apart, what technology is used during the processes, and how to get started.
Analytics and reporting have differing:
The Goals of Analytics:
Below lists the many goals and characteristics of analytic reports.
Focuses on the Why
Analytics concerns why things happen or why teams should take specific actions. It’s one thing to know what’s going on. It’s another thing to know why. Analytic reports allow viewers to understand the complexity of their environments and how their actions might impact it.
For example, a manager may look at reports and notice a constant downtrend in sales for the past few weeks. Through analysis, she can hypothesize why this might be and brainstorm how to combat it.
Interprets the Data
The analysis process is mainly when teams look at data models and make interpretations based on their prior knowledge, training, or business acumen. Interpreting data is what changes it from random facts to actionable information.
Raw data is valuable but unhelpful. Data reports are helpful but inconsequential. Analytics is both consequential and impactful. Data analytics reports aim to help teams understand the events they are witnessing.
Predicting Future Trends
Advanced analytic technologies provide predictive insight from historical data. Data analysts can use algorithmic and AI tools to forecast potential outcomes and run “what-if” tests. These instruments can show the possibilities for one action’s outputs versus another.
For example, the technology can use past data to predict what would happen if a company sold x product or y products. This type of analytics reporting could help management decide which product to invest in and what promotion strategies to apply.
Delivering New Values
Analytics reporting tools like R or SQL can run endless tests to answer just about any question scientists have. For example, they could pull a data report that shows younger demographics responding more favorably to their dairy-free products (reporting).
From this, they decide to alter their marketing strategies to push other plant-based products toward younger groups (analysis and actions). The possibilities as to what insight data analysis could provide are vast.
The Goals of Reporting:
Now that you understand reporting analysis let’s review the goals of data reporting. Data reports are a collection of graphs, charts, or diagrams that present qualitative and quantitative data in a palatable way.
Keeping Track of Day to Day Happenings
Day-to-day reports can be an invaluable asset to management teams. Reporting and data analysis on a consistent basis keeps businesses informed about what’s going on and aware of any changes they should take note of.
Many companies auto-generate daily performance reports, weekly balance sheets, or monthly expense reports. It increases overall awareness and keeps groups informed and on the same page. Frequent reporting can decrease the time it takes to raise a red flag about something potentially concerning.
Gathers Data and Presents It in an Organized Form
Reports are not simple reiterations of raw data. They are a complete formatting of its design and appearance. They provide a summary of numerous data sets, illustrating how they relate in a comprehensible manner.
Without reporting, data would be scattered across databases, leaving us unable to draw a single conclusion from it. After clear, cohesive reporting, analysis can be more meaningful and effective.
Lets You See All of the Data
Another important goal of data reporting is to collect related data in one communal location. This makes it possible to uncover correlations and relationships between different events or actions.
Seeing all of the information in one place paints a bigger picture of what’s going on. It also opens doors for further reporting, data analysis, and discussion.
Analytics vs Reporting: How to Tell Them Apart
You can see how analytics and reporting are interrelated but have distinct goals. Below are the ten main differences that illustrate how reports vs analytics differ. These will explain how reporting is more than charts and graphs, and analytics is more than reflecting on them. We’ll provide a more practical description of how the two look on the job, in real-world scenarios.
1. Business Definition
Within a business, it’s clear how analytics and reporting differ. Reports gather data, organize it, and display it simply. Many teams craft reports and analyze them together in meetings. Analytics provides valuable insights and recommendations on what to do next. Teams may see the data on a deeper level and collectively agree on an action plan based on what they’ve learned.
For example, a monthly performance report displaying sales revenue and call counts for each salesperson is produced. Using this report, each salesperson can analyze their performance and gauge where they stand amongst their peers.
2. Unchanged VS Dynamic Templates
Reports have a fixed amount of data to work with. You’re aware of what data is included in each report and through what time span or range of values. The report’s contents will reflect whatever data is available at the time, and the only way to acquire new visualizations is to run a different report.
Analytics and reporting differ in this way — analytics is not so fixed in scope. The process of reporting analysis is flexible and depends on who’s doing the analysis and in what context.
How Analytics Compares
Analytics is a dynamic process that is less restricted by finite data sets. Analytics reporting brings together separate data to find new relationships and meanings. You are limited to the existing reports but can run various tests on them, like if-then experiments, A/B testing, and comparative analysis. Analysts can perform real-time comparisons that uncover new insights about the same data sets.
3. The Internal Process
Reporting and analytics also look very different for business operations. Whereas reports organize, collect, and format information, analytics uses higher thinking skills to identify what it means. For example, a report may show sales on a downtrend, and analysis could identify the cause as improper marketing. Alternatively, reporting can show past seasonal sales trends, and analysis might conclude that certain products must be pushed at different times of the year.
4. Isolated Data VS United Data
Companies use several systems to complete transactions, internal operations, customer communication, and data collection. How can you gather all of that information in one place?
Data reporting takes on this role by running concurrent reports and collecting information into one cohesive report. These reports provide a knowledge bank of compiled data from various programs, creating unified information from isolated facts. Data scientists complete this reporting, and analytics piggybacks off of it.
How Analytics Compares
Now that the data has been collected, analytics reporting can study relationships between them. Successful analytics connect the dots between disparate data sets and discover novel ideas.
When information is laid out correctly, businesses can make informed decisions based on the entire scope of their operations, not separate entities. Reports and analytics bridge the gap between random factoids and meaningful insights.
Reporting and analytics may appear similar in nature, but their contents are quite dissimilar.
Reports are usually automatically generated using predetermined settings. This could look like a daily sales report, production numbers, or budget progressions. It may include charts, graphs, or whatever visual tool best suits the data.
Analytics presents data with patterns and relationship depictions. This could look like a graph showing the correlation between production and employee time off or inbound leads and marketing tactics. Data analysis reporting will identify relationships or cause-and-effect patterns.
6. The Main Users
Managers and department heads usually set up reports to be auto-generated at specific intervals. For example, a sales manager may set up a call-count report mid-shift so that salespeople know how much more they need to do. Reporting is helpful for employees at every level.
Analytics is typically completed by upper-level management, team leaders, executives, and decision-makers. They perform data analysis to understand the goings-on of their companies and create more innovative strategies—reporting and analytics work hand in hand to optimize everyone’s performance.
7. The Technology Used
Reporting happens with tools like Powerpoint, Excel, Google Analytics, or Oracle. They collect and organize sets of information into digestible visual aids. Most reporting tools have a feature allowing users to automate reports at their convenience.
Analytics can be done on the same programs or more sophisticated ones. These intelligence software go further, completing complex analyses and producing data analysis reports.
8. Original Data VS Modified Data
With reporting, you receive the same information in a different format or configuration. Whether you’re changing the order of columns into organized values or creating sophisticated visual aids, the actual data hasn’t changed. Unlike data analysis, reporting does not introduce novel information.
How Analytics Compares
On the other hand, analytics examines the data you have gathered and either draws predictions or finds out why things are happening the way they are.
You could, for example, test what would happen if you implemented a new procedure or estimate how long it would take for a project to be completed. Analytics reporting introduces new ideas.
This is accomplished by:
- Predicting future events
- Supplying new values
- Expanding on current information
How to Get Started with The Reporting Process
For relevant reports, you need accurate data in a workable format. There must be enough information to make a solid report.
The following aspects are necessary for a high-quality report:
- You have enabled real-time reporting
- Data is relevant and organized properly
- The technical data can be translated
- You understand the data’s context
- Teams are aware of which reports are helpful and which are frivolous
- Reporting dashboards are set up
Reporting is the first step of your data manipulation process. For powerful analytics and reporting, you must have a concrete data entry and organization foundation.
The Challenges of Reporting
There’s a reason many people go to school for data science. It can be challenging to interpret, especially when the format is in code or not-self explanatory. Most data is highly technical and vast — raw data is not easy to navigate.
There is a great deal of time and effort involved in data entry. Many businesses hire interns or entry-level employees to perform data entry so that managers can handle the reporting and analysis.
How to Start Using Analytics for Your Business
For effective analytics, you must have certain foundations laid. Sloppy data yields sloppy analytics reporting. Aim to have the following steps covered before you begin analyses.
- Create a hypothesis: What is the purpose of your analysis? What are you trying to find out? Hypotheses can stem from your reporting structure or be used to create new reporting structures.
- Use reporting to collect relevant data: This will help you stay focused on the issues at hand.
- Use analytical models: Models help us process information and make more sense of it.
The Challenges of Analytics
Analytics is more than plugging data into formulas. Sometimes you need to wait long periods to collect and organize enough data to draw meaningful conclusions.
Collecting data and building analytics strategies takes time. Also, your data may be too disorganized and inconsistent to get quality analytics reports. This means you’ll have to spend time reconfiguring and re-entering the data.
Companies also must be cognizant of data leaks and privacy concerns. Your database software must be secure enough to trust with the data.
Analytics and Reporting Examples
Let’s get into a few examples of data reporting and analytics in the real world. These illustrations will help you apply the above concepts to your business and industry.
We’ve used the three most common fields to show you what the process would look like. Keep in mind there are numerous ways to go about reporting and analytics — don’t stop at these three.
Example #1 – Sales
Reporting metrics for sales would reveal:
- Number of new customers
- Customer origins (how many used a free trial versus signed up outright)
- Customer acquisition cost or onboarding investment per customer
- New revenue
- Monthly sales revenue and profit
- Salesperson rankings
- Salesperson call counts, meetings scheduled, or other KPIs
- Average sales cycle length
- Average customer age at cancellation
- Quote to sales ratio
- Average transaction value
With this information, sales managers can use reporting analysis to increase productivity or reduce costs.
Sales analytics would reveal:
- Success rates of different sales tactics
- Which vertices lead to the highest customer retention
- Which sales representatives have the highest/lowest customer retention
- Predictive analytics to forecast quarterly revenue
- Sales trends analysis
- Pipeline analysis for note at what point customers must convert
- Customer demographic information
- Sales effectiveness (to know when to step in and assist faltering salespeople)
Sales managers can use analytics reporting to better attend to their sales staff and set them up for success.
Example #2 – Business Finance
Business finance reports might reveal the following:
- Sources of new revenue
- Expense reports
- Cash flow balances
- Profit margin levels
- Payables versus receivables
- Profitability per account
- Profitability per department
- Turnover rate
- Shipping expenses
- Outstanding balances
- Credit limits
Business finance analytics would reveal the following:
- How turnover rate varies across departments in relation to management styles
- Which accounting techniques are the most effective at preventing collections
- How profitable are sales across regions and demographics
- Best methods to decrease shipping costs
- How to reduce costs in the least productive departments to avoid layoffs
These analytics reports help executives make decisions to better their financial standings.
Example #3 – Marketing
Marketing reports could show the following:
- Amount of leads by source
- Amount of qualified leads by source
- ROI per marketing campaign
- Customer acquisition cost
- Conversion rate by ad/landing page/commercial
- Advertising spend
- Website traffic
- Bounce rate
- Organic keyword rankings
- Ad views versus clicks
- Posts with the highest social media engagement
- Follower demographics versus target
With accurate marketing reporting, analysis can be used to increase campaign effectiveness and reduce unnecessary costs.
Marketing analytics would show the following:
- What campaigns are generating the least ROI and why?
- How to prevent wasted advertising spending
- When to target different demographics to increase effectiveness
- What is the best time to create social media posts?
- Predicting how new commercials will be perceived
- What areas show room for improvement?
- Are there gaps in the market that we could fill?
Using quality reporting, analytics can answer higher-level questions that raise the bottom line of marketing agencies.
As we’ve shown, analytics and reporting serve different but overlapping purposes. They’re both essential to everyday business objectives and play crucial roles in the improvement and efficiency of employees at all levels.
Reporting uses visual aids to display data with the goal of explaining what is happening. Analytics uses high-level intelligence to identify patterns and discern why things happen, what might happen in the future, and how to change them.
At Profit Stack, our goal is to provide readers with cost-saving tools and practical business knowledge. If you’re interested in trying new data modeling software, check out this article on the best data modeling tools that details different software options you might not have seen before.