In 2009 I had the opportunity to work with the VP of Field Marketing at a leading security software company. Much of the project involved analyzing the “big data” collected by different systems that supported the marketing (Eloqua), sales (Oracle), and channel functions (Excel) and trying to “connect the dots” between the upstream marketing programs and actual business closed by sales downstream in the pipeline in order to understand the effectiveness of the marketing strategy.
The challenge of trying to piece together the big picture across data silos was more than familiar to me. The supply chain had already demonstrated the power of tearing down the walls between logistics, production, purchasing, and engineering silos. Industries like high tech continue to lead the way in further extending this “silo busting” philosophy further upstream into their supplier base via similar “design chain” principles.
So why not apply the principles of Operational Excellence to the demand chain?
What most people don’t realize is that many of the Operational Excellence concepts and principles proven on the supply side are also relevant on the demand side – as summarized in the table below:
The paper which resulted from this analysis (which you can download here) takes these concepts and puts them into the sales and marketing context. It makes the case for a demand chain approach that shifts the focus away from functional silos and towards improving the flow across the end-to-end process (a la “contact to contract.”) Just like how supply chain focused on increasing the velocity of material as it moves through different stages (raw material, work-in-process, finished goods), why not apply the same principles to different stages (leads, opportunities, closed) of the pipeline?
In other words, if leads were “virtual inventory”, how do we apply this thinking to create value? The following is an excerpt from the paper that uses the 5P framework to expand on the inventory concept:
- Process: Who ordered this inventory? Sales? Product Marketing? Channels? Why was it not consumed? Who is accountable for unused/obsolete inventory? Are there clearly defined quality control [acceptance] criteria from Sales? What happens to rejected inventory? Are they discarded or reworked? How/where are “reject reasons” captured? Can the surplus be offloaded to capacity in Channels?
- Policy: If Marketing is measured on [New Leads] inventory, then who owns the rework inventory [Nurturing process]? How do you “age” this inventory before they are removed from the Demand Chain due to obsolescence? Are we “pushing” or “pulling” demand – in other words, what kind of business are we in?
- People: Who owns the resources [Telemarketing] to perform the rework? Marketing? Inside Sales? Is this capacity treated as a fixed cost? Does outsourcing this operation convert it to variable cost? Will outsourcing bring better inventory accountability?
- Platform (Technology): How does the CRM system designate accepted vs. rejected inventory? Does it enforce the chain of custody by forcing the creation of opportunities from the existing leads inventory (and prevent the duplication of leads)?
- Performance: What data is the system collecting to improve Lead Quality, Cost, and Time? Where and what are the constraints to the pipeline?
In the four years since this paper was written, I have watched marketing automation platforms mature to where technology is no longer the obstacle to embracing the demand chain concept. Rather, it is more a question of People and Policy – in other words, do we have the right leadership who can tear down the walls between Marketing, Channels, and Sales and align these silos? After all, if you think back 20 years ago, there was no concept of the supply chain, much less the existence of an executive position that had responsibility for the end-to-end process. So why not an executive in charge of the “demand chain”?
Seriously, why is the disconnect between sales and marketing still the #1 topic of discussion in the blogosphere? If we aren’t ready to challenge the traditional rules that reflect long-held assumptions and beliefs as opposed to being data-driven and committed to continuously improving processes, then maybe its time to let the engineers run sales and marketing?