Turning Data into Information (Part 1)

Data and business have traveled hand in hand through the ages. Before the first great stories were recorded in writing, traders and businessmen were chiseling numbers on stones to keep records of their transactions. The days of the stone tablet have long since passed, and the data that was once recorded on them have gone digital – in a BIG way. The sheer amount of data that can or is collected has given way to a vast industry of new and improved products, innovative approaches, and three letter acronyms.

What is Data?

Most of you can skip right down to the meat and potatoes of this post, but it does a service to the points being made to define data. Merriam-Webster offers three definitions of data:

Definition of data

  1. factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation
  2. information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful
  3. information in numerical form that can be digitally transmitted or processed

Data is raw, unorganized facts that are typically collected with the intention of discussing the data and using it to make better decisions in the future (i.e. turning it into intelligence).

Data can be qualitative or quantitative.

Every business owner loves a bit of quantitative data because it is easy to collect, analyze, and understand. How much profit does an item make? When are you the busiest? Which employee has the highest sales?

Qualitative data is a little more of a complex beast and is usually collected through a variety of surveys. Customer satisfaction surveys are an excellent example. The Business Dictionary states that qualitative data “describes” while quantitative data “defines”.

Population versus Sample Data

Collecting population data is incredibly complex and expensive. It represents all possible measurements or outcomes that are of interest. This could be feasible where 20 employees make up the total “population” of an office. The vast majority of data is collected on a sample basis. This means that a portion of the total population is used to represent the population as a whole. An example of a sample study might be a customer satisfaction survey of 100 customers that came to a particular location in a given month.

Why Should I collect Data?

The simple answer: Small businesses should mine their data because it’s an asset they already own.

They can use existing data to glean market insights for long-term strategy and more granular customer insights. This information can be used in aggregate to generate reports or studies to educate internal teams or customers on best practices, as well as to develop targeted product roadmaps. – Erik Severinghaus, Simple Relevance

Most of us know that giant companies like Google collect data on a massive scale. Google uses data to refine search results to better match your interests, among other things. Amazon uses your prior purchases to recommend additional items that you may be interested in buying. We know the big guys can collect and utilize data, but why should small business owners worry about collecting data? The answer is that small business owners can always improve efficiency and effectiveness. The only way to improve is to look at the data, convert it to information, and make future decisions based on that information.

  • Find out who will buy and when
    • If you are looking at each individual’s purchase separately then you are missing the big picture. Look at the data in a spreadsheet and compare all the available variables to determine the characteristics of your current buyers so that you can decide on the best market(s) for your business.
  • Develop new or existing products that are desirable
  • Identify quality marketing and advertising opportunities
    • If you are not already using Google Analytics for your website, then you are missing out on a gold mine of valuable information. CMO reports that 72% of millennials research and shop their options online before going to a brick-and-mortar store. (If you are already looking at your Google Analytics, look out for our next article on what you can do with all that wonderful data that Google has been collecting for you!) Google has recently introduced a variety of tools that help physical stores track the number of online or mobile conversions took place based on ad dollars spent.
  • Help future customers or clients
    • Let’s say you offer a dog grooming service and you’ve decided to start asking customers to rate their experience with each groomer. If the majority of clients with Poodles say that Tom is the best, then you know that sending someone with a Poodle to Tom will most likely result in a happier customer who is more likely to return.
  • Drive growth
    • “What gets measured gets managed” – Peter Drucker
  • Monitor marketing and advertising ROI
  • Generate long-term insights
  • Generate loyalty
  • Make informed decisions

(Read more: Top Reasons Why Small Business Owners Should Collect User Data, Just how well do you know your customers? By Carolyn M. Brown)

Still not convinced that data can do anything more than slow down your systems? Check out the Huffington Post’s article: What Can You Do With Data? by Shelly Palmer or Symmetry’s What to do with the Data? by Manuel Gnida.

Before Collecting Data

The critical question to ask is not “How do I collect data” but “Why am I collecting data?” If you cannot answer that question, then no amount of data will ever be beneficial. Data collection is the process of gathering and measuring information in a systematic fashion that enables one to answer stated questions, test hypotheses, and evaluate outcomes. Deciding on the Why will help you determine the How and What of data collection.

Simple questions that can be answered through data collection and analysis:

  • What did I sell and when?
  • How much profit did I make on this or that?
  • Who came into my store?
  • When am I the busiest?
  • How much did I pay in labor last quarter?

More complex questions:

  • Are my employees more productive in low-light or high-light environments?
  • Is my revenue impacted by a certain disruptive technology?
  • Does this new product appeal more to Millennials or Baby Boomers?
  • How much does it cost me for my delivery drivers to sit in traffic?

Michael Overly with CSO has this recommendation: Think Carefully Before Collecting Data.

Stay Tuned for Part 2 of Turning Data into Information