How to optimize a business’s earnings?
When we think about growing our core businesses a few things come to mind: increasing sales, targeting new markets and continually launching new products.
But there’s a type of growth that doesn’t get the credit it deserves and that is the potential increase of earnings that we can get from experimenting with new pricing and business models or from cost improvement initiatives.
A continual improvement of the business operations is like a discipline that you religiously practice and get better at over time. It becomes part of your culture and could evolve into a serious advantage when competing with less disciplined incumbents.
We cover each these optimizations in more detail next.
Optimizing revenues
We mentioned earlier that a few years ago Rolls-Royce launched a pay-per-use program for their Jet engine products called TotalCare, where customers would pay for every hour of uptime delivered instead of buying the engines for a large upfront cost.
To make this business model work, Rolls-Royce collects operational data from the customer engines to predict their performance and to create preventative maintenance schedules that seek to maximize uptime and minimize disruptions (since they are now paid based on uptime).
This is a good example of how a business model made products available to a market that couldn’t stomach hefty upfront acquisition fees but that can swallow a more digestible pricing model, increasing Rolls-Royce’s revenues along the way.
No need to say that those revenues would be going into a competitor’s pocket otherwise if Rolls-Royce hadn’t come up with this option.
In a similar move, some companies use price to penetrate a market segment that would be otherwise unreachable.
Apple, for example, offers its Music service to students in eligible schools at half the regular price, helping Apple compete with Spotify and Pandora for the young adult space.
Arguably, a good portion of those students will eventually convert into permanent users of the service after college.
Recent advancements in data analytics and predictive models are now making it easier to experiment with multiple options and customize pricing based on a buyer’s individual characteristics.
For example, AXA, the global insurance company, is using machine learning to analyze driver data like age, residency and vehicle type along with the user’s driving history to predict the chances of having large loss accidents and pricing its insurance policies accordingly to reflect those risks.
Mass customization, micro-experimentation and price discrimination are all possible now and they can all be of great help in trying to increase the top line of the business.
Optimizing costs
On the cost side, you must be always looking for opportunities to improve your overall business performance and find better ways to use the resources of your organization, especially people and money.
This goes beyond the classic view on cost reduction where managers monitor productivity changes and act reactively to correct deteriorating performance.
What we mean by cost optimization is actively finding ways to reduce costs in a meaningful way, making your operations leaner and producing a positive net effect on your bottom line.
While it is true that some cost reductions may lead to a productivity drop, we say that as long as the tradeoff seems to deliver a positive net effect to your bottom line, you should pay attention and deliberately decide what to do about it.
There can be subtle inefficiencies that get so embedded in the culture that sometimes you can’t even see them.
To spot opportunities for cost improvements, our recommendation is that you imagine a very cost-conscious investor buying your business for big dollars.
If that was the case, which costs would that investor immediately get rid of to justify the high acquisition price tag? How would that investor optimize the way things are currently done?
When you look at the business through the eyes of an external observer whose job is to improve the way things are currently done, you can move beyond personal and emotional attachments that may be preventing you from seeing better ways of doing things.
Just to give you an idea, there are four areas that new owners would normally investigate to reduce costs in a newly acquired business: non-key personnel, operations and the optimization of debt and taxes.
The optimization of the organizational structure, i.e. personnel and staff, is probably the most conflicting and sensitive topic of this list because of the personal attachments we may have to the people there, but as an executive you must be upfront about it and address any inefficiency without hesitation if you really want to succeed and be profitable in the long run.
That’s what you are paid to do.
The general rule is that overheads should continually go down, as you get deeper into learning curves and age your value chain, but never the other way around. If you think about it, the more experience you accumulate in a process the fewer people you should need for it.
Another way to reduce overhead costs (per unit) is by increasing the utilization of fixed assets, for
A restaurant that is only open during lunch and dinner, such as Chipotle Mexican Grill (NYSE: CMG) in the United States
The more you use the facilities, the lower the costs of each unit of revenue produced by those facilities, which increases business profitability.
Inefficiencies and poor performance should never be allowed in any business and must be dealt with vigorously.
Leaders must always be on the lookout to find the optimal way of running things and keep people accountable for their performance.
There are only three ways to deal with poor-performing businesses. They must be fixed, sold to a company that puts a high valuation to them (one that can build synergies with the business or that can fix it), or they must be closed.
There’s no other way around it, only the “fix, sell or close” options that Jack Welch popularized in the 1980s.
With respect to operations, you have to go beyond operational effectiveness.
First, you must be a cost leader in everything you do by implementing the best practices out there. It doesn’t matter if your strategy is not based on low prices, you must always do things at the lowest cost possible and never ignore inefficiencies.
When it comes to financial costs such as debt and taxes, you must also dig relentlessly and extract every drop of savings possible. Believe me, sometimes there’s a lot of value hidden behind financial loopholes and gray areas.
You must always be looking for cheaper sources of debt and replacing them as needed. Sometimes you may get better deals just by telling lenders that you are shopping around for other offers to replace their debt.
Finally, bringing in a third party from time to time to propose cost optimization plans may provide fresh views on your company’s operations, and is a good way to mitigate the risk of being trapped within comfortable bias zones.
Using data analytics to improve earnings
Data analytics is increasingly becoming one of the most powerful technologies at helping executives optimize costs and revenues. Companies now use data analytics tools to analyze customer and operational data and suggest improvements.
Probably the most well-known example of data analytics being used to boost sales comes from Amazon’s product suggestions algorithm which makes recommendations based on a user’s individual behavior on the site and their purchase history. In one of its patents, this is how Amazon describes its personalized shopping algorithm:
“A computer-implemented service recommends items to a user based on items previously selected by the user, such as items previously purchased, viewed, or placed in an electronic shopping cart by the user…”
“In one embodiment, the service generates the recommendations using a previously generated table that maps items to respective lists of “similar” items. To generate the table, historical data indicative of users’ affinities for particular items is processed periodically to identify correlations between item interests of users (e.g., items A and B are similar because a large portion of those who selected A also selected B). Personal recommendations are generated by accessing the table to identify items similar to those selected by the user. In one embodiment, items are recommended based on the current contents of a user’s shopping cart.”
On the cost side, there are many ways in which companies are using data analytics to boost their profits. UPS, for example, developed a prescriptive analytics model called ORION (On-Road Integrated Optimization and Navigation) to provide turn-by-turn directions to drivers, minimizing mileage and fuel on delivery routes.
This application has avoided over 100 million miles and saved 10 million gallons of fuel, a combined saving that exceeds $400 million every year, which as with all other cost savings drops directly to the bottom line.
Data analytics tools, when well-developed, can help you improve business performance by helping you:
- Understand customer behavior to improve offers and customer service,
- Identify cost optimization opportunities,
- Identify opportunities for new offers, and
- Identify the decline of an industry by monitoring margins shrinkage, price reductions and a drop in product usage.
In our opinion, there are two key reasons why companies must now explore the implementation of data analytics applications.
First, because some of these applications are still relatively new, they can still provide an edge if competing with companies that haven’t yet found a way to implement them.
Second, analytics applications usually get better over time, as more data is collected, analyzed and provided feedback on, making the “experience curve” of the application a differentiator by itself.
Kind of the same effect as an aged value chain as we reviewed earlier.
That’s why data analytics tools are always best if implemented sooner rather than later, since those taking the lead now will have the most intelligent systems of the future, and may build serious barriers for later entrants, just with the amount of data collected alone.
References:
Wu, Sun. Strategy for Executives, this book can now be downloaded for free here.
Bhattacharya, Arindam; Reeves, Martin; Lang, Nikolaus; Agustinraj, Rajah. New Business Models for a New Global Landscape. The Boston Consulting Group. The New Globalization Series. 2017. URL: https://www.bcg.com/en-gb/publications/2017/globalization-new-business-models-global-landscape.aspx
Sato, Kaz. Using machine learning for insurance pricing optimization. Google Cloud website. March 2017. URL: https://cloud.google.com/blog/big-data/2017/03/using-machine-learning-for-insurance-pricing-optimization
Davenport, Thomas; Harris, Jeanne G. Competing on Analytics: Updated, with a New Introduction: The New Science of Winning. Harvard Business Review Press. Kindle Edition.