“How can I grow my business? How can we scale?” These are the common question I got after my talk on micro, small, and medium enterprises. Almost in unison, these companies expressed apprehension, at the same time, optimism, on what is in store ahead amid threats and opportunities presented by digitization, changing consumer preferences, and entry of new competitors,
There is reason to be worried. Nine out of 10 startups fail, according to a Fortune survey among founders of failed business ventures. While locally we are seeing the strongest resurgence of the startup craze since the dot-com era, we will not see them all succeed commercially, and most likely the failure rate is a lot higher.
Why do they fail despite the plethora of business incubators, venture capitalist funds, and courses on entrepreneurship?
In previous articles, I argued that lack of preparation and skill to scale a business in a shortest time and limited resources is the main reason why new business ventures fail. But behind these activities is having the right metrics to measure the health and success of the business.
The problem is, entrepreneurs mostly rely on financial indicators like revenue, sales, and profit as metrics to measure the success of their business. But these have limitations.
Consider these financial metrics as what you see in the rear-view mirror of your car. You see them only after you pass by them. They’re in the past and you can’t do anything now to change them.
These financial metrics examples are what we call lagging indicators – those that follow an event, in other words, it’s after the fact. They are typically “output” oriented, easy to measure but hard to improve or influence.
A more mundane example is in weight loss as a personal goal. If you’re trying to lose weight, a lagging indicator is simply the number you always see on the weighing scale each morning. But how do you actually reach your goal of losing weight? Surely it won’t happen by just weighing every day. Rather, you need a weight loss plan to reach your goal.
This is where leading indicators come in. These are typically “input” oriented, hard to measure but easy to influence. In the weight loss example, there are two leading indicators – calorie intake and calories burned. These are easy to influence but hard to measure. Ordering food in a cafeteria does not give you the immediate calorie count. On the other hand, you don’t have a clue on the calories you burn without any measuring device.
But you can still somehow measure your calorie intake using a mobile app that needs inputs on the food you eat, while calories burned can now be estimated using wearable devices. The important thing is that measuring these on a regular basis will give you an indication of your future weight lost. It also changes your behaviour to eat less and exercise more.
Similarly, a business needs to have leading key performance indicators (KPI), apart from lagging ones, to forecast the success and health of the company. These KPIs are a way to give you the power to look ahead and see where new opportunities or challenges might await and to change course when necessary.
Examples of leading KPIs to indicate a company’s future growth are percentage growth in sales pipeline, percentage growth in new markets, number of new patents, number of app downloads, number of new customers acquired, and number of unique website views.
While leading KPIs can forecast the business’ future growth, solely depending on them can pose dangers.
For example, a growing sales pipeline is a great indicator of the future growth of a business, but if this is not converted to actual sales revenue, then it will mislead the business owner.
Hence, there’s a need to have the right mix of leading and lagging metrics to ensure a balanced view of the future of health of a business. The entrepreneur should correlate the input leading metrics to the output lagging metrics, and evaluate patterns that can predict the future growth of a business.
With advances in computing and technology, both lagging and leading metrics can be part of a predictive analytics model to have a more accurate forecast of the future. It’s important to learn and understand how to make its predictive analytics algorithms more accurate by identifying leading indicators as business metrics. Effective predictive analytics platforms based on real-time leading indicator data go far beyond traditional lagging-indicator data, fueling accurate predictions of future events, incidents, and business growth.
The author is CEO of Hungry Workhorse Consulting, a digital and culture transformation consulting firm. He is the Chairman of the Information and Communications Technology Committee of the Financial Executives Institute of the Philippines. He teaches strategic management in the MBA Program of De La Salle University. The author may be emailed at firstname.lastname@example.org.