How to see the 4 stages of the information cycle

Follow the four "I"s to make better data-driven decisions in your organization

Quick summary:

• To make sound decisions, you must make good use of all available information

• The information cycle provides a 4-step framework for dealing with data

• First, information is incomplete and must be gathered from a variety of sources

• Second, as information is acquired, it is often inconsistent and conflicting

• Third, information that is incorrect must be discarded to resolve discrepancies

• Lastly, people must interpret information to make sound data-driven decisions

We are drowning in data, yet decisions are difficult

My grandfather was an engineer and an educator who worked on developing radar at MIT during World War II and later served as the Dean of Engineering at Syracuse University for many years. As a child, we would drive from Michigan each summer to the farm he had purchased in upstate New York to spend a week with family. The farmhouse was relatively small, and I distinctly recall the maze in the dining room and living room areas created from the stacks of magazines, newspapers, and books my grandfather read. He would often share interesting facts and stories on a wide range of subjects with us in conversation, and he passed this love of news and media down to my father, who continues to subscribe to several newspapers and magazines today. While my father’s place does not have a maze of magazines, his dining room table has been taken over by stacks of periodicals. (Occasionally, I wonder if my dad is single-handedly responsible for keeping some of these publications in business!)

While most of us don’t subscribe to as many newspapers and magazines anymore, we still consume lots of information about the world in our personal and professional lives, primarily online. I won’t spend much time in this article discussing the ills of misinformation, propaganda, and “alternative facts,” except to recognize our need to be mindful of the information we consume.

In my grandfather’s time, there were fewer sources of information. Much of what made it to his farmhouse was filtered and curated by writers and editors in hidden ways. I don’t mean to imply there was anything nefarious about this, but the reality is that publishers come with biases, just as all humans do. They also faced economic realities - media is ultimately a business and needs to earn revenue from subscriptions and advertising. These incentives can skew the coverage that’s provided in the publication. While the ethos of news gathering was a “just the facts” mindset and desire to “show both sides,” a simple review of the vastly different editorials found over the years in the Wall Street Journal and New York Times shows that even well-respected newspapers can come to vastly different conclusions based on the news.

The four stages of the “information cycle”

Previously, I have written about the importance of relying on information to shape strategy and managing your information diet to find a healthy balance. In this article, I want to share the concept of the four stages of the information cycle. It is self-evident that we are gathering data and information continuously in our daily lives and business, and this process is never complete. The fact that information gathering is a continual process can make decision-making challenging: the temptation for “analysis paralysis” is real. However, the opposite is also true and more prevalent in my experience: people are prone to jump to conclusions and taking action despite not having enough information. Humans are pattern-recognition machines; we see a set of facts emerging and instantly compare that with our prior experiences to make judgments. The more experiences we have, the quicker our minds make judgments - often ignoring other data that contradicts our instincts or remaining unaware of what additional facts are needed. We are “predictably irrational,” in the words of Dan Ariely: we constantly make the same mistakes due to factors such as confirmation bias and the availability heuristic.

To combat our instincts and built-in biases, I recommend following these four stages:

1. Incomplete

We start the process with incomplete information and must gather data, facts, stories, and images to fill in the gaps in our knowledge. Since we are unlikely to obtain all possible data points when making a decision, we must start the journey by identifying the critical gaps in our understanding and continue to refine this list as we acquire more and more information. Many people use the analogy of an onion: to find the core, we must peel back one layer at a time. Some information is readily available, while other information is more difficult to obtain. Identifying the most impactful sources to use is a crucial step in the gathering phase.

2. Inconsistent

The next stage in the cycle is identifying the areas where the information you have gathered is inconsistent. The fact that some of the data is in conflict or not in alignment is not necessarily a bad thing. If all of the information you have gathered is always consistent, it is likely a sign that you need greater diversity in your sources. When information conforms nicely, it tends to support a particular ideology that may be logically consistent and tells a compelling tale but is not grounded in reality. Be wary of stories that are too tidy. Embrace the messiness and seek to go further in the information cycle to sort out the discrepancies.

3. Incorrect

Once you have identified inconsistencies in the information you have gathered, the next step is to find out which parts are incorrect. Some of the information you have is wrong, misleading, or out-of-date. Just as children who play a game of “telephone” rarely relay the original message correctly at the end, there is a high likelihood that some of the data needs to be discarded, updated, or revised. Be sure to capture how and when mistakes are made and adjust your gathering procedures. Perhaps you’ll find that some outlets are unreliable or that specific sources work best in combination. Finding and fixing inaccuracies and discounting unverifiable information is essential in finding the proper way to weigh disparate data when making decisions.

4. Interpret

Lastly, once the process of gathering, reconciling, and curating information is completed, there is a need to interpret what it all means and decide on actions to take. I think back to my early days working as a research assistant at the Federal Reserve Board and the myriad of economic indicators I monitored. Some data series were more reliable than others, and we placed more weight on specific observations. However, when all the available data were considered together, a clearer picture of the economy began to emerge that would inform decisions on adjusting interest rates and monetary policy to drive economic growth while keeping a lid on inflation. Economic data was vital, but we also relied on stories from sources such as the Beige Book compiled from different regions across the country. In addition, there were robust debates among the many Ph.D. economists who worked at the Fed about what all of the information meant for policy, and different interpretations were common. Finally, all of the information, including interpretations from the staff, was summarized and packaged together for the Chair and members of the Federal Open Market Committee (FOMC) to debate before a final vote was taken on whether rates should be adjusted.

Use innovation to fill in information gaps

I’ve written extensively on innovation in the past for Forestview (you can check out the complete archive at your leisure). I firmly believe that a major reason to pursue innovation efforts is to help you make more informed decisions. When looking to shape the future, there is a dearth of information that makes it hard to make an informed decision. By identifying information gaps, designing small experiments to answer critical questions, and gathering valuable data as part of your overall objectives for a pilot or project, you can significantly reduce risk by reducing the number of unknowns.

A great example is a small blockchain initiative I was involved with at a previous employer. We did not know much about the technology and there was a wide range of opinions - mostly uninformed - on whether or not it presented a significant opportunity for our firm. Fundamentally, we could not provide any sort of estimate on the potential financial impact: it could have been worth $30,000 or $300,000 or $3 million or $30 million or $300 million. We honestly had no idea! Because of the large amount of unknowns and upside potential, it made sense to make small investments around pursuing blockchain initiatives to help us learn and clarify whether a larger investment was justified and how it should be prioritized alongside other capital investments. By positioning innovation initiatives to be primarily about learning and discovery, not return on investment, you can gain a lot of valuable information at low cost that helps you make better decisions about the future.