Whether it’s implementing a business strategy or taking a family vacation, we all want to plan accordingly. We try to rely on analytics and intuition. We look at business trends in an attempt to make educated decisions and we check weather forecasts hoping we won’t get stuck in the rain. And, with so much technology and Artificial Intelligence (AI) are our fingertips, the ways in which we can make these assessments are abundant. But, how can we know what the best strategy is? When is Analytics most reliable and when should we ignore technology and stick with our instincts?
When it comes to predictable events, Analytics is fantastic for providing insight and additional analysis. Currently, there is significant hype for new AI tools. GPS, improved forecasting, trend analysis, and selection have all experienced dramatic gains. I am amazed, for example, how GPS systems monitor traffic and predict an arrival time. However, it’s noteworthy to ask ourselves if we’re simply using them for efficiency and ignoring important considerations. This is one of the problems of using analytics and intuition.
There are two questions we must ask when using AI and Analytics:
- First, are the assumptions, data, analysis, and conclusions really valid?
- Second, do we limit the use of intuition and small measures in using these tools?
One of the biggest issues with AI is that we simply accept the results because they are impressive or too complicated to understand. We need to review the validity of the data, measurement, and analysis.
For example, the pandemic will require adjustments for data analysis. How do you compare changes from 2019 to 2020 and 2020 to 2021? In particular, how do you forecast 2022 and beyond? How important is an annual average and should you use 2019 or 2021? The analysis is highly dependent on issues like assumptions, demographics, time periods, etc. The answers can also be more dependent on a specific situation rather than general rules. Forecasting things like workers going back to the office, students going back to the classroom, airline passenger growth, business meetings, entertainment, and apparel trends all have different parameters.
We frequently just assume cause and effect when the relationship can be nonexistent. Statistics make it very easy to assume that a relationship among factors is a straight line. However, most relationships involve a variety of factors, as shown in the chart below:
Significant issues with analytics and intuition also occur when intuition, risk, and low probabilities produce better results than analytics. We all know the lottery is a bad bet, but some people do win. Similarly, many billionaires like Gates, Bezos, Jobs, and Must have achieved fame by pursuing high-risk and out-of-the-box alternatives. Many analytical recommendations encourage the “most likely” rather than the best alternatives.
More importantly, the reality is that outliers create much of the innovation, excitement, and change in our society. Steve Jobs probably said it best: “The people who are crazy enough to think they can change the world are the ones who do.”
In their new book, Noise, Daniel Kahneman, Olivier Simony, and Cass Sunstein point out how Analytics can fail to include key metrics. For example, mood, bias, mental state, etc. can alter judicial decisions. Variables like hunger, how much sleep we got, and personal preferences can all affect decisions.
While using Analytics based on AI has limitations, here are several suggestions to make it more effective:
Keep the goal in sight to improve your decision-making. The goal of Analytics is to improve decision-making and identify great alternatives. Focusing on satisfying investors, suppliers, employees, etc. is simply an invitation to long-term problems. Similarly, you need to understand the goals, timeframe, and precision in your research. Are you simply trying to make a living in a short time or build a giant business that you know will lose money in the first few years?
The biggest problem with decision-making is bias. Whether we admit it or not, we all have biases. Analysists love to discuss mathematical formulas and measurement in affecting bias; however, most bias (especially in small businesses) is simply human. For example, our most recent experience can have a significant impact on decisions.
Keep it simple. Simplify wherever possible. Focus on factors that really affect your business so you can understand them and estimate factors that are not as significant. For example, look at aggregate costs and administrative expenses rather than trying to forecast small items like telephone, utility, and insurance costs.
Be more open. Organizations need to be open to measurement and feedback. Observing, understanding, and sharing financials, operations reports, and sales reports is the first step.
Develop, test, measure, and adapt. Many plans, forecasts, and proposals are done in a static format with one-dimensional analysis and results. Often, these end up being flawed because we live in a more dynamic and interactive world. For example, branding, marketing, pricing, and operations must all be viewed as an integrated program rather than separate and isolated activities. Remember the 80-20 rule, which states that 80% of your sales will come from 20% of your products and/or customers. Are you measuring your sales, key items, and customers?
Embrace change. Don’t just talk about change. Take action! Responding to disruptive change like the pandemic requires finding a way to incorporate data, analysis, and pre-existing models while also embracing out-of-the-box thinking and flexibility.
Don’t neglect key elements of success. Operations, customer service, and logistics are just as important as traditional functions.They present huge opportunities for a business to become more efficient and differentiate itself (i.e. selling on Amazon or bundling products).
Relax. You can’t do everything in one day. Pace yourself and remember that there will always be uncertainty and change. Stay focused and take it one day at a time.
Always be willing to improve. What are your biggest challenges? Where are you overlooking potential opportunities? In what areas could you do better? Remember: more Analytics is generally useful for small businesses; however, one must be sure the foundation, reliability, data, and processes of the Analytics have a firm base.
Understand diversity. Demographics are affected by age, location, socioeconomic status, race, gender, etc. Current events have certainly affected trends relating to racial and female groups. Staying up-to-date on your target consumer and their habits will help inform your decisions. Do you know who your customers are and what demographics they belong to?
Analytics provides astute insights for business decisions and should not be underestimated. However, its value is highly dependent on how effectively it is used and the recognition that intuition is still an important factor. In particular, the more creativity and uncertainty involved in any given situation, the more intuition will be required. It is important to use both analytics and intuition.