Analytics To The Rescue
Is Analytics The Answer?
This is Part 1 of a two part series on when analytics is most helpful. See part 2 for more on advanced analytics.
Can analytics solve your business problems?
Wondering if more data will help?
Not sure if it’s worth the time and effort?
Let’s explore when and where data and analytics is most useful.
Where Basic Analytics Can Help
When faced with a business problem it can be hard to know whether data and analytics can help solve the problem. There is currently a lot of focus on advanced analytics, but because simpler is often better, let’s start by looking at several situations where basic analytics can help.
You Need to Verify Facts
Analytics is extremely helpful when you need to quantify a situation, like how many new hires leave your company within the first 6 months. This is the most basic form of analytics, but verifying facts can help you identify and understand a problem better. It’s fairly common for company beliefs and ideas to be treated as facts even if they were never grounded in data. Not all beliefs and ideas are quantifiable but those that are should be verified.
You Want To COMPARE GrOUPS
Analytics can help when you want to evaluate differences between groups like divisions and product lines, or compare your company to other companies. You may want to compare the attrition rate of one department to another, or of your company to an industry benchmark.
You Want To understand how something changed over time
Analytics is key if you want to understand whether something has changed over time or identify important trends, like whether the attrition rate has changed over time and if so is it higher or lower than in prior years.
You Want to Evaluate A Relationship Or Understand patterns
Analytics can help you understand whether two things are related to each other. You might want to understand whether profit margins and the number of clients per sales manager are related; do sales managers with a lot of clients have higher margins or lower margins, or is there no connection? You can learn a lot from these relationships, but you’ll need an analyst with a good understanding of statistics to ensure that you are finding real relationships. It’s actually common to find relationships in the data that aren’t real. These are referred to as “spurious correlations”.
You need to Establish Metrics and Standards
Once you have verifiable facts and you’ve explored trends and relationships you’ll want to know what these mean for your company. You need to understand whether you should be concerned about what you found and if you need to take action. Analytics can help you set metrics and standards to evaluate what if any changes are needed.
These methods largely fall under the category of descriptive analytics. They describe what’s going on and can provide insight into possible reasons for your business challenges. This can provide some or all of the information that you need to solve problems and make business decisions. A data analyst is a good choice for this type of analytics as long as you are not dealing with extremely large data sets or real time data.
Should You Proceed?
Now you know more about analytics methods and where these might be helpful, but how do you know when it’s cost effective?
Analytics can be extremely valuable: it can help solve problems and save time and money. However, more data and analysis isn’t always the solution. Analytics can be expensive since it may require special systems, tools, and talent. This is especially true of advanced analytics.
In order to focus your resources on more cost effective projects, consider the following steps for evaluating the cost-benefit trade off of analytics projects.
Understand the Problem
Start with a clear understanding of the problem. Not having a clearly defined problem from the beginning often results in wasted time and money. Defining your problem usually requires a combination of business and data analytics knowledge to understand both the business context and possible analytics solutions.
How Expensive is the PRoblem?
How expensive is the problem you’re trying to solve? If it’s minor and inexpensive it may not be worth investing the resources needed to fix it. On the other hand, if it’s a costly problem it may well be worth the investment needed to address it.
Where’s the Data?
Is data readily available to support or refute factual information and assumptions? Can you verify that the data is available and clean, and that it’s been used before. If not, this can substantially extend your timelines and increase costs. Be sure to investigate data availability before moving forward.
Verify basic facts and Assumptions
Often just verifying basic facts and assumptions can quickly determine if there is a problem and further define it. Sometimes anecdotal evidence can kick off a quest for a solution when there isn’t actually a problem, or it’s only a temporary or minor problem.
Evaluate the Level of Effort AND Resources
Determine what type of analytics you’ll need and how complex the analysis is. Advanced analytics will likely take longer and cost more, as well as come with a range of uncertainties. Consider if this is really what you need.
You’ll also need to identify the resource needs and whether you have these resources in house. Finally, since business context is key, you’ll need people with business knowledge involved in the project, so you’ll need to estimate the level of contribution needed from various departments.
Making The Most Of Basic Analytics
There are many areas where data and analytics is very useful for understanding and solving problems. This post covered basic analytics, including verifying facts, comparing groups, evaluating relationships and patterns, and establishing metrics and standards. It also looked at how to evaluate the cost effectiveness of analytics projects.
Don’t underestimate the power of good descriptive analytics. However, there are complex business questions that require advanced analytics solutions. My next post will cover this topic.
How are you using analytics at your company? Are there areas where you’d like to be doing more but you’re not sure how to get started? Contact me at firstname.lastname@example.org to find out how Ariel Analytics can help.
About the Photos: Rocky Mountain National Park, Colorado
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