Why Reporting Is Not Analytics & How To Make The Transition
By Carmit DiAndrea, Analytics Consultant
Reporting is not analytics. Read that again. It doesn’t matter how great tables and charts look, how fancy the graphs and visualizations are, or what credentials the dashboard designer has. Reporting is (still) not analytics. From a purely functional perspective, reporting aims to answer questions of quantity – how many calls did we answer, what types of calls did we answer, how long were those calls, how long did customers have to wait to reach an agent, what was the average quality score on those calls, how many of the calls handled were resolved, etc. This is known as descriptive statistics, statistics which answer questions along the lines of ‘what happened?’ or ‘what is happening?’ Analytics aims to answer more complex questions like why did it happen, how can we predict the next time it’s likely to happen, how can I prevent it from happening in the future? The key difference between reporting and analytics is an understanding or at least a hypothesis regarding causation.
As an example, a call center analyst might report out daily on call volume handled by a queue. Whether the report is a table of daily, weekly, or monthly numbers or a visualization of a trendline over weeks, or even a control chart, it is still merely a report. It provides visibility into what happened. This same analyst might notice that call volume on a specific queue has been rising steadily for the past dozen weeks. This same analyst may do a quick calculation and realize that the rate of increase has been close to 300% over those dozen weeks. These observations still fall under the category of ‘what happened’ and therefore still constitute reporting. It is when this analyst, or anyone else for that matter, begins investigating the ‘why’ that we transition from reporting to analytics. Even if the investigation leads to more questions than answers, we’re now operating in the arena of data analytics.
Why does this distinction matter? Because nomenclature and semantics create a set of expectations, and regardless of whether or not the expectation is correct, performance against expectations is what distinguishes between success and failure. Organizations are drowning in data, yet starving for insights. Reporting does little to solve the insights problem s analytics can deliver insights that enhance knowledge and drive change and, in some cases, even transformation.
If you happen to own a reporting team (or a reporting team that has been mistakenly named an analytics or business insights or business intelligence team) and you would like to transform it into an analytics team, there is a roadmap for doing so successfully. The 2 largest challenges in making this transition will be time and skillset.
- Step 1: Assess the reports your team is generating. You may find that some of the reports are no longer being used. Eliminate them and save your team some time. You may find that some (if not all) of the reports can be automated, if not significantly streamlined. Create the time/space for the reporting experts on your team to automate as much as possible. Not only will this reduce the opportunity for human error, but it will also gain your team time, time that they can then spend conducting an analysis.
- Step 2: Assess the skillset of your team. Do you have a team made up of people who are top-notch in working with Excel, Access, SQL, Tableau, Power BI, and other query-building, reporting, and data visualization tools? Do you have a team of people with skills in SAS, R, SPSS, MATLAB, RapidMiner, or similar statistical analysis or data mining tools? Do you have individuals with a little bit of each? Or do you have a combination of both? As you transition from reporting to analytics, you will still need team members (with a reporting skillset) who can maintain and trouble-shoot reporting that has been automated, you will still need team members who can query databases and provide datasets for analysis, but the skillset of the team will need to shift more heavily towards an analytic skillset.
- Step 3: Prioritize areas of the business in need of analytics. Most likely all parts of your business can benefit from analytics. The question for you will be where to start. You might start with the largest area of your business. You may choose to start by aligning to strategic or transformational initiatives. You may want to start by taking the reports that have the highest level of executive visibility and appending to those (now automated) reports analytics.
- Step 4: Partner, partner, partner. As an analytics team, your ability to impact the business will be entirely dependent on your ability to effectively communicate the results of your analyses and motivate people to act on your findings. Without action, analytic insights are meaningless. Help your internal clients understand how they engage with your team, set expectations for what an engagement or project might look like, and partner with them to measure the financial impact of your recommendations and their actions.
The most important thing to remember in making this transition is that analytics is a far more time-consuming venture than reporting. Whereas reporting is like following a recipe (get data from location X, Y, and Z, perform calculations 1, 2, 3 and visualize using chart type Y), analytics is more like a fishing expedition – you know the approximate area in which to fish, but you don’t know how long it’s going to take to catch a fish, you will need to sift through some junk that may initially look or feel like a fish but turn out to be an old shoe, and you may need to move between a few different spots within your target area until you find the right fish (a finding that is meaningful & actionable). Understand this change in time investment, plan accordingly, and set appropriate expectations with your stakeholders.
Carmit DiAndrea is a contact center, analytics, and Speech Analytics expert with over 20 years of experience translating customer feedback, operational, and contact center data into business strategies that transform organizations. Carmit is also an educator, teaching statistics, research methods, and algebra as an adjunct instructor at Kaplan University and is the lead instructor of the Speech Analytics MasterClass (speechanalyticsmasterclass.com)
Concentra Solutions maximizes contact center performance through Quality Assurance, specializing in Compliance and Customer Experience. We partner with internal and outsourced contact centers to provide insights and recommendations to drive performance and operational improvements. For more information, visit www.concentrasolutions.com.
About Concentra Solutions Inc.
Concentra Solutions maximizes contact center performance through Quality Assurance, specializing in Compliance and Customer Experience. For more information, visit https://concentrasolutions.com. Follow us on Facebook, Instagram, LinkedIn, and Twitter.
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