Finding Decision-Driven Growth From Within

The topic of growth remains a top priority for every executive. In a recent Gartner CEO survey, 53% of executives stated “growth” as a top priority, a whopping 20% higher than the number two and three priorities of “digitization” and “corporate structure & development” respectively.

To achieve growth, CEO’s are pouring capital into initiatives that help them identify new growth opportunities (“Where to play” projects), spending millions on new analytic capabilities to help execute better (revenue growth management, promotion optimization), acquiring the “next” big brand and a slew of other initiatives.

If you ask an executive about the success of these initiatives, you will undoubtedly get a response that includes the words, “mixed bag”. The reason? The quality of the decisions made in the development of these initiatives. In fact, almost ¾ of executives say they make good decisions as frequently as bad ones. According to the McKinsey Organization Insight Survey, 72% of senior-executive respondents said they thought bad strategic decisions either were about as frequent as good ones or were the prevailing norm in their organization.

The opportunity cost of these poor decisions is massive. In a 2019 Gartner study, the firm found that on average, S&P500 companies can improve EBITDA by as much as 3% (absolute increase by improving decisions (They measured good decisions vs. bad decisions based on exception rates and a few other factors). This is a nearly 30% improvement based on average EBITDA of S&P500 firms, or a $700 billion opportunity in EBITDA expansion for the S&P500. This is to say, while executives must continue to look externally to achieve growth targets, there is a massive opportunity to achieve growth by simply looking within! The quality of decisions, and the decision-making process within organizations must become a top priority for companies to remain competitive. This plays out in the data. According to a Bain & Company Global Retooling Survey conducted in 2020, they found that “decision leaders”, companies with a high decision effectiveness score, outperform peers by an average of 4.8x on total shareholder return, 5.5x on Total EBT growth and 4.1x on total revenue growth over the five year period between 2014 and 2018.

Organizations are bad at making decisions

When you ask employees, only 20% believe their firms excel at decision making (source: McKinsey Organization Insight Survey – Decision Making in the age of urgency). Why is this the case? Both human and organizational factors play a role.

From a human perspective, cognitive biases are a key driver. These include availability heuristics, anchoring, confirmation bias and many others. This is of course a relatively new field of study pioneered by behavioral economists like Daniel Kahneman, Amos Tversky among others. Many resources exist to better understand these elements and how to mitigate them.

From an organizational perspective however, we find key inhibitors to optimal decision making caused by several factors (non-exhaustive):

· Data to Decision Disconnect: the data available never makes it to the actual “decision table”, and is not considered as a factor

· Coordination Collapse: Today’s decisions are complex and require cross-functional teams working together. The increase in remote work has relegated key decisions to be made via a disparate collection of emails, spotty Zoom connections and a limited view of “the big picture” – all factors hurting effective decision coordination

· Declining institutional knowledge: Growth in the transient workforce, shorter employee tenure negatively impacts the organizations “know-how”

·Lack of Learning: Companies do not record or track the decisions they made, how they made them and therefore, cannot learn and improve in the future

Executives should work towards improving these issues by taking a systematic approach and improve their decision processes.

Decision-Back

So how can companies improve their overall decision-making ability? By implementing a “Decision-Back” approach. Sales and marketing leaders often push the view of being customer-centric as thinking “Customer-back”. In a similar manner, decision makers across the organization should think “Decision-back”.

Decision Back is a relatively simple concept. We believe that Decisions are the most valuable asset of a company, and therefore, a companies’ planning, research and other go-to-market activities should be framed around the decision to be made. Rather than asking, for example, “is my brand connecting with consumers”, we should be elevating the question to the level of decision such as, “Do we need to optimize our creative”. The former question is important, but outside of the context of the decision to be made, it doesn’t add much value as it is not actionable.

The Decision Back approach can be simplified into four key steps and summarized in figure 2 below:

1. Start by articulating the business decision to be made. If it is in the form of a question, ask yourself, “if we answer this question – what can we do about it” – is it actionable? Does the question get to the heart of an issue, or is it really part of a bigger problem we are trying to solve? Often times, a good practice would be to first write down what the situation is, what is the complication, or change that warrants us to make a decision, and then from there, we can better articulate the decision.

2. Create a “decision tree” Identify the sub-questions that help inform the decision to be made. As a basic example, “Should we change price”, sub-questions may include things like, “What is our strategic objective”, “How will customers react”, “What will our competition do”, How will our distributors react” and so on. These sub-questions should be unique to each other, but put together, represent all elements that may influence a decision. Management consultants often refer to this as MECE, or mutually exclusive, collectively exhaustive. An important note: when we refer to a decision tree, we are referring to a visual representation of decision drivers and not a statistical model. Figure 3 below provides one such example:

3. Only after a decision tree has been created, and all key drivers and sub-questions have been mapped out, should we start to collecting data and connecting them to the respective sub questions. By having a clear list of sub-questions to be addressed, we will be much more efficient in data collection, analysis and research activities.

4. The first three steps are all about structuring and collecting information to help make the decision. The final step is of course to make the decision. Now that a decision tree is created, we see all key factors that need to be addressed. Cross-functional team members are assigned specific “branches” to complete, and the team works together to synthesize information, come to conclusions, and work back up to answer the decision itself.

This Decision-back process is similar to a traditional management consulting approach in that it Is a systematic way  to develop recommendations. The key difference however, for executives, is how can they implement this process across the organization, and not just on ad-hoc consultant driven projects - but for all important decisions.

Executives should be implementing decision enablement systems, or decision systems of record to facilitate such a process. Our firm, Clearbox Decisions inc., has developed a platform called Cloverpop to do just that.

These decision systems of record allow us to go back to previous decisions, track how they did vs. expectations, understand where things went well and most importantly learn and disseminate decision best practices across the organization.

One of the big pushbacks that we hear to such an approach is, “but we can’t forget about the politics that go into decisions”. Corporate politics are nothing new. Many managers approach decisions with a view of what is best for the organization as well as themselves. While this may be true, it is the decision facilitators job to come up with the best recommendation and the final decision owner will have to execute. However, the process itself promotes transparency which we believe, over time, will reduce political bias.

Once implemented, the “Decision-Back” approach leads to significant benefits that can’t be ignored. These include:

Better Decisions

·   Consistent approach to decision making

·   Comprehensive view of all key drivers of the decision

·   Actionable – recommendations can be directly acted upon

 Efficient Execution:

·   Speed to decision – Teams are able to come together and make decisions in nearly half the time

·   Less Waste – Time and data / analytic investment waste is significantly reduced as teams no longer “boil the ocean” to come to a recommendation

 Smarter Team:

·   Employee Engagement - Increased transparency allows Team members to see their contribution within the decision-making process

·  Knowledge Capture - Decision ”know-how” is captured in the decision bank (database) to improve institutional knowledge, reduce impact of employee turnover

· Reduce Bias - Structured decision-making process reduces systematic error and group think

In conclusion, we believe that executives must elevate “Decision Making” as a top priority for corporate improvement. The current lack of process, tracking and learning leaves too much opportunity cost on the table to be ignored. The Decision Back approach, when implemented can lead to better decisions, made more efficiently and improves the overall team engagement and buy-in.