You’re coming off of a recent product launch, and the first year showed tremendous potential. You exceeded your revenue targets, and you’re ready to raise prices. Is it the right time?
Or perhaps you want to consider the other side of the profit equation and explore ways to cut costs. Where do you start? Will your product’s quality suffer?
Of course, there are no easy answers to these questions. But running a series of simulations or tests can reduce uncertainty. At worst, it will help you identify trends that offer you direction.
What if there were a framework you could rely on to consistently deliver objective data to help you decide your next move?
A few organizations, typically those rooted in traditional research and development, live and die by the scientific method and have a robust capability to scale experimentation of ideas. Most firms have learned that formally testing an idea may require more investment than is comfortable for their leaders.
Improved access to data and modern analytics has executives yearning for data to guide them in their strategic decision-making. However, without validating that your firm has the right talent and expertise to properly plan, set up, and run the test (let alone analyze the results, interpret the data, and draw reasonable conclusions), you may end up feeding your leaders bad intelligence. Make the investment up front to build and mature your internal testing capability, and it will pay significant dividends in the long run.
Whether you’re looking to enter a new geographical market to boost sales, when to launch a new product to maximize revenue, which message to use in an advertisement, or which projects to cut funding for, proper experimentation will help you make sound decisions.
Use these pillars to build a foundational skill within your organization to test your ideas. Once you have a few wins, build on that positive momentum to develop a full-blown experimentation capability.
What doesn’t get measured won’t get done. Similarly, if you can’t objectively point to a metric that addresses your problem statement or hypothesis, you’re not showing results. In most cases, you can find a way to measure it or can connect a few proxies to get close. Some objective measurements are required before you can even think about effective experimentation.
Talent and expertise
When it comes to the scientific method, you need a good handle on statistics. Do you need a PhD in statistics to be able to produce results that are reliable in practice? Hardly.
But it’s important to have sufficient statistical expertise to do more than just make sense of the data. You need an expert to translate the data to ensure that the business leaders who are making the decisions understand the reliability of the data, confidence levels of the output, and caveats on the conclusions.
Identify a small test to get a sense of which direction to move in. Admittedly, a full-fledged experiment requires a good amount of time and resources, so, before you dive in, see if you can justify it in advance with a small-scale test.
Positive results from ideation are few and far between. You’re going to see uninspiring findings far more often than you’d like. Innovation is tough. But this is why you need a well-thought-out process to ensure that you have:
- a diversified portfolio of tests;
- an operating model that allows you to identify the right objective metrics; and
- an appropriate communications plan to keep executives and stakeholders abreast of your progress.
You don’t need every idea to be a winner. But a robust methodology that yields reliable results will ensure that the few that do win will have an exceptional impact on the business.
Share the wealth
Incorporate a way to share successes, failures, and lessons learned. Some organizations penalize failure, which discourages the free flow of information and ideas.
To cultivate an environment of ideation, it’s critical to allow your team the freedom to explore and vet their ideas, to provide them with the proper tools and resources to test them, and to incentivize your teams to openly share their experiences so that the firm doesn’t repeat mistakes and can capitalize on the ideas that will move the company forward.
A firm that thrives on this kind of communication is more likely to turn a lesson learned for one employee into institutional knowledge across the firm.