- Become more aware of your bias. The best line of defense against cognitive bias is awareness. There are tools like the Ladder of Inference or the Process of Abstraction which you can use to understand your thought process that can lead to a wrong conclusion.
- Celebrate inclusion to truly harness collective genius. Make sure when you need to make a decision, you are not just looking for people who will say what you want them to say. Look for people who have different opinions and learn about their perspectives. When you do this, you have a diverse perspective, and this is the absolute key to the importance of diversity in the workplace.
- Leverage systems thinking and lateral thinking methods in an organization to expose and recognize unintended consequences with your decisions. Systems thinking is a technique of analyzing relationships between various elements of a system. Rather than breaking down a system into elements to analyze separately, look at the entire system and how each element balances or reinforces other elements.
Author B.J. Neblett once said “We are the sum of our experiences. Those experiences – be they positive or negative – make us the person we are…and those [experiences] yet to come, continue to influence and reshape the person we are, and the person we become.” This concept can and should be applied not only to individuals but also to organizations making data-informed decisions. The more experiences and perspectives available to an organization, the better and more complete picture it has, the fewer blind spots exist, and the better-informed decision they can make.
When trying to make data-informed decisions, everyone usually has the right intentions to make the best decision from their perspective. But what can you do to try to avoid blind spots? You can be aware of bias that may exist in your decisions, and you can seek diverse perspectives in an inclusive manner.
- A data strategy that includes how the organization handles data quality, data management and data governance. Individuals need to trust the data.
- An analytics framework that provides the organization with the right set of analytics based off what their need is. This can range from having a measurement framework that analyzes key performance indicators, to running predictive analytics and machine learning models.
- A robust learning program to help all employees understand the fundamentals of data as well as how to increase their data literacy.
- A decision making framework, process, and methodology that the organization can use systematically and systemically to ask the right questions, analyze the right data, and make decisions leveraging that data and their experiences.
- A robust learning program to help all employees with the right soft skills required to work with data. This includes systems and enterprise thinking, critical thinking, relationship building, active listening, and communicating with data.
- An environment that safely fosters cognitive diversity, curiosity, challenging assumptions, and failing fast, fixing fast, and learning fast.
There are many risks associated with the increasing amount of data available today. These risks can have a negative impact and can cost organizations millions of dollars in lost opportunities and added costs.
These risks can be organized into the following categories:
- basing decisions on data that is incomplete, incorrect, or not trusted
- basing decisions on incorrectly built and interpreted visualizations and analytics
- making biased decisions
- making ineffective decisions based solely on data
- making ineffective decisions due to the organizational culture
- incorrectly communicating decisions
- basing decisions on data that may be unethical or illegal
We are living in a truly unprecedented time. One that is, and will continue to, radically change the way we work, the way we live, and the way we communicate with each other. This is the dawn of the fourth industrial revolution.
The first industrial revolution used coal and water to make steam to mechanize. The second industrial revolution used electricity to mass mechanize and mass produce. The third industrial revolution leveraged electricity to bring about the rise of electronics both to miniaturize (microprocessors) and automate (automatons and robots). The fourth industrial revolution includes technology breakthroughs like machine learning, IoT, 3D printing, nanotechnology, biotechnology, energy storage, and many more. And what powers all of this? Data. Need more proof of the value data will play? IDC predicts that by 2027, data will be something that can be valued on a company’s balance sheet.
What really makes this unprecedented is the speed and scope of the changes occurring during this revolution. The speed of which this is happening is exponential compared to previous industrial revolutions. The advancements in cognitive and machine learning alone are literally happening at inhuman speeds. The scope is much broader as well. It is impacting and disrupting just about every industry and doing so in just about all parts of the world.
The overwhelming potential of this to positively impact society, including both the global economy and the quality of life for all of us, is massive. Think about all the benefits data can have on society globally. It can help understand and defeat diseases and minimize impacts from injuries. It can help anticipate and prevent crime. It can improve educational performance and outcomes of students. It can help prevent conflicts and instability. It can help reduce racial profiling and make people aware of the importance of cognitive diversity and harmony. It can help protect our heritage, help solve global warming, help sustain natural systems and resources, and prevent extinctions, even our own.
Sure, there are downsides with this speed and scope, including things that need to get broader attention like data compliance, governance, and the ethical usage of data. One of the biggest concerns is the fuel that drives these innovations (data) is something we are becoming increasingly dependent on leveraging. In many situations, too much emphasis is placed on the technology alone. Technology is not the lifeblood of the fourth industrial revolution, it is the people who are interacting with the technology and the data inputted and outputted from it. It is imperative people have the right skills. This requires more people to be able to read, work with, analyze, and argue with data.
One other reason this is unprecedented is because the right skills needed are a combination of both hard skills and soft skills. People at all levels of an organization, in all parts of the globe, need to have the hard skills to understand data, including how to visualize and interpret it. They also need to be able to use soft skills to challenge data with problem solving, think critically and collaboratively to avoid bias, they need to be able to make systemic data-informed decisions, and then be able to communicate those decisions using data to their stakeholders.
This is all moving so much faster than previous industrial revolutions have that organizations, including businesses and schools, are behind and need to catch up fast. The set of skills required are lacking. Institutions that educate on the comprehensive set of skills as a unified curriculum are few and far between.
As I progressed through my work career and through my life, I started to recognize the importance of the question ‘why’. I started to learn about systems thinking and everything started to look more like an inter-connected system rather than vertical silos. In work, every performance problem did not appear to be a result of the individual or their lack of knowledge. Most importantly, decisions started to include other perspectives. I started to see how all this positively impacts organizational culture, diversity and inclusion, and how it increased innovation and made for better decision making.
Decision making can be a complex process, which requires a lot of information to be processed simultaneously; making it a very complicated computational task for the brain. Studies show that there can be up to 11 million pieces of information thrown at the brain per second. But the brain’s conscious level can only process about 40 pieces of information per second. To solve these problems, we rely on simplifying heuristics, or intuition, rather than logical reasoning. This has helped humans make decisions quickly and helped humans survive and evolve in the primitive days. The risk of this is that at times irrelevant, contextual information leads to making inconsistent, illogical, and implicitly biased choices. This risk is now magnified since we are in the age of digital transformation with constant change and technological advancements. We are still fighting for survival, but now survival from ourselves and our own destruction. Decisions leveraging data are now more important than ever.
When making data-informed decisions, it is critical to look at the information from multiple perspectives. This is easier done within a group of diverse colleagues. It allows you to easily reframe by listening to other perspectives. To one person, the answer may be to stop delivering a product in a specific segment. Another person with a different set of experiences and personality will most likely have a different perspective that will help you make a better data-informed decision. The key being that the group is not just demographically diverse but also cognitively diverse.
We are still learning about the human brain, and we are still evolving as a society to be conscious of our implicit and unconscious bias. Current events have taught us that this is still a topic that is not getting enough emphasis and awareness. Hopefully over the next few years, we will see signs of change: less stories of kids in their formidable years being teased or alienated for being “different” and less stories about racial profiling. From a business perspective, I hope to see companies move the needle with innovation by leveraging a diverse group and embracing different perspectives when making data-informed decisions.
It’s about how to make data-informed decisions. Data-Informed Decision Making is the ability to transform information into actionable and verified knowledge to ultimately make business decisions. Learn about our unique methodology for data-informed decision making.