Why are analytical skills important?
A 2013 AMA/i4cp study found that:
—58% of company leaders say analytics are important to their organizations
—82% say they will be important in five years
However, only one quarter of the companies in the study felt they were equipped to meet today’s analytics needs. Two of the reasons companies need greater analytical skills are:
—A massive influx of data
—Less expensive but more powerful technology that will enable a future increase in the use of Big Data
Organizations with fully developed analytics skills—the ability to organize, analyze, and communicate data that can be applied to their human capital and not just to the other elements of their business—will continue to be the top performers in the years to come.
If you want to help your organization become more competitive (and enhance your own career in the process), here is some basic information about analytics from AMA’s seminar Improve Your Analytical Skills: Making Information Work for You.
Improving your analytical skills will help you:
- Apply techniques to information to help determine what is relevant
- Put information into a form that can be analyzed
- Analyze information in order to identify the “best” opportunity for your business, and explain your reasoning
- Recognize patterns, and discern what they can mean for your business
- Identify a framework as the basis for creating presentations that use information you’ve derived from your analysis
What is Analysis?
We are flooded with information and new knowledge on a daily basis. Assimilating, organizing, and analyzing it is crucial for strategic planning and decision making. Analysis starts with identifying the right question to answer. Determining the essential information for your audience is imperative to forming conclusions and recommendations and then explaining what the analysis revealed. By stating a main idea and summarizing key points we create a successful analysis that focuses on solutions, strategies, and recommendations for success.
The foundation of making data work for you is an understanding of key concepts in the analytical process. Analysis is the ability to visualize and articulate concepts based on available information, whether this information is written, verbal, or presented in a media source like videos or pictures. It involves skills like synthesizing, discerning patterns, and distinguishing important information from less important information.
The core of analysis is evidence. It helps you to understand a question, problem, or situation; evidence supports your conclusions. Analysis deals with seeing patterns and drawing conclusions from both quantitative and qualitative data.
Quantitative vs. Qualitative Data
Quantitative data refers to information that can be expressed as a number, percentage, or calculation. Here are a few examples of quantitative data:
—Quarterly sales results
—The number of products purchased in a particular time frame
—The number of patients seen
Qualitative data refers to information that describes attributes or meaning. Qualitative data is useful in an analysis to help you determine why something is so. Here are a few examples of qualitative data:
—Color, texture, appearance of a particular product
—A customer’s motivation to purchase one product over another
Qualitative data is often captured via research interviews, surveys, and questionnaires. It can also be obtained through social media sources (tweets, online product reviews, etc.) that encourage participants to write their answers in free form. During an analysis of qualitative data, you may need to determine what percentages of answers fall into a specific category. In order to do this, qualitative data is often converted to quantitative data.
Both types of data are valid types of measurement: each type can tell you different things when completing an analysis.
Another key term in the analytical process is Data Analysis. Data Analysis is sometimes thought of as transforming data into knowledge or information. The purpose is to draw conclusions or make recommendations. The analysis techniques are simply tools that can be applied to help understand the data. But the core process is a mental one. Analysts need to look at the data, think about it, and relate it to the problem they are trying to solve and the answers they are trying to obtain. For the vast majority of straightforward business problems, the only analytic techniques that are required are counting (tabulating), comparisons and determining general tendencies, which usually translate into averages.
Content analysis is a systematic way of reviewing and summarizing text, whether it is delivered orally, in writing, or via multimedia. Content analysis is used to:
—Classify information having common characteristics
—Identify trends, key themes, highlights
—Analyze language in context
—Compare information from various sources
Data Analysis and Content Analysis are processes that occur in all analyses.
Analysis Process: PAC Model (Plan, Analyze, Conclude)
Sometimes the word “analysis” can connote a lot of work, effort, and “brain power.” We perform analyses all the time, even when we’re not aware of it. The PAC Model provides a framework for conducting a thorough and meaningful analysis. Depending on the analysis, you will go through these steps in a matter of minutes, sometimes over the course of hours, days, weeks, months, or longer.
Define your purpose
Clarify the question
Decide on your approach
Collect and organize your data
Evaluate the data
Report your results
The AMA/i4cp Analytical Skills study concludes, “The gap between where organizations say they are in terms of analytical abilities and where they would like to be is great. The next step in taming Big Data is closing that distance by drilling down to where those specific deficiencies are in different workforce segments. It is not sufficient to have analytical ability sequestered within traditional, number-crunching departments. Analytical ability must be strengthened throughout the organization, especially among human resources personnel and within the executive team.”
The need for analytical skills is growing. The time to amp up your staff’s and your own skills in this key area is now.
© Copyright 2013 American Management Association. All rights reserved.
Find out more about how you can improve your analytical skills.
Download “Conquering Big Data: A Study of Analytical Skills in the Workforce.”