This is my inaugural column for MarTech, and it’s great to be here.
From T-shaped marketer to translator of business languages
For more than 30 years, I was a marketer and communicator in large companies and agencies. In my quest to be seen as significant, I became what HR teams call “T-shaped.” I gained more understanding about other functions and how the business worked. It’s made a big difference in my career, but I think it may be making the biggest difference today.
About a year ago, a CEO introduced me to his team with a Venn diagram. It showed me at the center of five interconnected circles representing different business functions: CEO, CFO, CRO, CMO and CDO. This illustration perfectly captured what I’ve always done — translate between these functions, speaking their unique languages to bridge gaps in understanding.
Speaking different languages: A common disconnect
Recently, I participated in a roundtable discussion with finance and data science leaders. It quickly became clear that although everyone used the word “predictive,” they meant very different things.
For data scientists, predictive refers to machine learning-generated forecasts based on patterns. For finance teams, predictive means causal forecasting — what’s expected to happen given specific variables.
When finance teams use the word, it means a forecast, ideally a causal calculation that tells them what’s probably going to happen under a certain set of circumstances.
For example, in climate change:
- Machine learning prediction: “Given a pattern of monthly temperature increases, next month’s temperature is predicted to rise.”
- Causal forecasting: “Due to 127 factors contributing to warming over the past three years, we forecast an X% rise per year, factoring in which elements are likely to increase.”
By pointing out this disconnect in terminology, both groups experienced a huge “lightbulb moment” and adjusted their conversations.
Moving back and forth between functional perspectives will be a hallmark of what I intend to share with the MarTech community. My goal is to use my experience to help ignite some new conversations between marketing, customer success, and communications — three global professions full of individuals who have taught me so much – and the rest of the business.
Dig deeper: How marketing ops can learn to speak C-suite
The forecasting train is coming: Is B2B marketing ready?
Let’s get to the nitty gritty and discuss the tunnel that B2B marketing finds itself in and how that bright light at the end is an oncoming train.
What exactly is that train speeding toward us? I’m talking about the increasing demand for marketers to issue guidance about their forecasted impact on the business.
After years and years of not being real, it’s real now. Nothing will reveal the truth of marketing as a powerhouse of effectiveness like the simple act of forecasting its business value.
Dig deeper: Measuring marketing’s impact: From metrics to growth
Issuing FY 2025 marketing guidance
As we move into 2025 budget planning, it’s time to get serious about the age-old tension between “What was your value this year?” and “How much should we give you next year?”
If you’ve worked in a public company, you know that many CEOs and CFOs have to provide annual guidance to investors, which is essentially a stick of expectations against which the next four or more quarters can be measured. Companies are starting to reinvigorate their use of budgetary business cases, focused on the same annual guidance and quarterly updates they give shareholders.
C-suites want a more transactional relationship with all functions, including:
- An annual forecast of their causal impact on the business.
- Analytics that enable them to compare that forecast with actual performance across time.
This is particularly critical when there’s a lot of time lag separating the expense from the associated value that the company gets back. It’s time for that to be the case in all the functions of your company.
Nonlinear multipliers: Why marketing’s impact is different
The need for this is particularly acute for functions that are nonlinear multipliers of business performance. Marketing, product development, IT, data science and HR are five examples.
These functions do not rely on a pro rata distribution of a pre-set performance goal that’s spread across a number of people or program spend. Their value is the extent to which they multiply the performance of other teams.
Sales is an example of a linear function, where the revenue target is divided across a certain number of people, regions, stores, etc. A hallmark of a linear function is that its performance can be represented on a Bell Curve. If you double the revenue target, your CRO will want to discuss a plan to double the sale team.
Why is this relevant to forecasted guidance? “Nonlinear multipliers” are functions where “Q1 spend” does not typically deliver any Q1 benefit. Indeed, the booking of expense and the recognition of value are often offset quite considerably in time.
The more typical “linear” relationship between expenses and benefits does not exist in these functions. Instead, they deliver specific leverage that cannot be created any other way. It’s crucial to understand that in advance because the implications are big.
B2B marketing is a great example. The marketing budgets you’re about to spend in Q4 of 2024 will not have any measurable impact on sales for at least two quarters. That gap is both innate to how the function works and is significantly influenced by external marketplace forces (i.e., headwinds and tailwinds).
If you’re facing a headwind, you’re going to have to do more to overcome it, just as when a headwind makes an airline pilot burn more fuel at a faster rate to remain on time. Airlines use causal analytics to forecast these scenarios, guiding their teams on how to make better, faster decisions and act more effectively.
Dig deeper: How to clarify marketing metrics to impress the C-suite
Forecasting: A new reality for marketing
Being able to understand the cause-and-effect relationships in your business will help you build high-quality internal forecasts that improve your external guidance, particularly for functions like marketing that have such a profound effect on sales’ ability to do more deals (revenue impact), bigger deals (margin impact) and faster deals (cash flow impact).
It’s time for functions like marketing to issue forecasted guidance to the C-suite so the leaders have a better understanding of what they can represent to shareholders and investors, as well as internally with other teams.
I know that many marketing leaders will recoil from this. But speaking as one who did it for 15 years as a functional leader, after you start forecasting your effects on sales performance, you’ll wonder why you kicked the can for so long.
Why? Because when you run the analytics needed to issue the forecast, you’ll discover it’s very likely your team is making sales about eight times more effective and five times more efficient than sales could be by itself. That’s the norm.
The post Why marketing benefits when it provides forecasted guidance appeared first on MarTech.
