How To Implement a Zero-Based Budgeting Strategy

My work with companies around the world, paired with access to a robust collection of academic research and case studies, has enabled me to create a matrix of best practices for implementing a zero-based budgeting (ZBB) strategy. And like any good list of things an organization should do, there are always a few things not to do.

One of the key reasons organizations are revisiting the ZBB philosophy is because we now possess technology that can bring the full force of ZBB into play. One of the causes of ZBB’s failure 40 years ago was the lack of proper tools.

Today, tools can report data on a real-time basis at the transactional level across a wide array of systems. You are no longer dependent on trying to make real-time decisions with out-of-date or incomplete information.

Getting Granular

With ZBB, the value is in the details. With access to data at the most granular level, you can find previously undiscovered and profitable revenue streams and uncover true costs. The ultimate goal is to take data, convert it into information, transform that information into knowledge, and share that knowledge with the business to support smarter, faster decision-making. By choosing the proper technology platform, diving into the details across the enterprise (both financial and operational), and communicating effectively to the entire organization, you can use ZBB to support a better decision-making environment.

What You Should Do

As I often say, there is no such thing as too much communication. This is especially true when you are trying to fundamentally change the way an organization thinks about something as far-reaching and close to its core as budgeting. And make no mistake: communicating on this scale will require a lot of hard work. Management will have to capture the hearts, minds, and hands of the organization. They must be willing not only to “talk the talk,” but also to be open and public about “walking the walk.”

What You Should Not Do

A word of caution. Two areas where organizations have stumbled are a) permitting too many exceptions to the ZBB framework, and b) failing to embrace an aspirational and visionary view of what ZBB can do.

When you introduce opt-outs to ZBB, you undercut the legitimacy of the process. The more you are willing to leave out of the ZBB rigor, the more people and functions will try to be exempted. You then end up with a final product that, instead of comparing apples to apples, is comparing apples to oranges. The decisions you make out of this improperly configured process may not only be suboptimal, but may even have negative consequences for the organization.

Not aiming high enough when designing and implementing the ZBB framework can end up leaving too much value on the table. We are absolutely in a transformational time, and the advances in robotic process automation (RPA), machine learning, artificial intelligence, and predictive analytics are real and will only become more important over time. You can’t be thinking only about where your intelligent FP&A (iFP&A) teams are today. They need to be building technological advances into their planning going into the future.