Big Operations and The Automation Myth

Big Operations and The Automation Myth

February 2024 | Digital Transformation

Sprawling tech stacks mean that business departments now own more applications than IT. Do business teams have the skills required to manage their apps?

Publicis used their recent quarterly earnings release to promote themselves as an AI platform company, stating that "everyone within Publicis will become a data analyst, an engineer, an intelligence partner, with all the information they need at their fingertips to supercharge client growth." I would expect the truth of those claims to reflect Publicis's status as the world's third largest advertising firm. As a vision statement it is compelling, but is it actually achievable?

Scott Brinkler of backed Publicis's claim, offering as evidence a recent report by Workato on the types of users building integrations using the Workato low code integration platform. The report is an interesting one, that highlights the gap between the AI hype touted by Publicis as compared to the dawning corporate reality.

The Right Mix

More cynical folks have spent the past year arguing that no amount of AI can turn everyday business users into data experts or analytics gurus. I would also argue that it's undesirable to do so. Businesses are successful when they employ a broad mix of people with different strengths and different backgrounds. Forcing every white collar professional to become an AI expert or data analyst risks the debilitating effects of groupthink.

Instead, a more accurate statement by Publicis would say that every business team will need to have a data analyst, an engineer and an intelligence partner alongside their day-to-day responsibilities. Those skills could belong to different individuals or they can belong to the same person. The real narrative is about the increasing importance of operations teams within business departments and how they are taking on many of the responsibilities traditionally owned by IT - including developing integrations. Nowhere is this more true than in marketing.

Big Operations

In many organisations, application ownership has become the responsibility of department heads rather than IT. A distributed technology stack requires each department to recruit administrators with the expertise needed to manage their application portfolio, many of which are highly sophisticated. Big data has added another layer of complexity, requiring a separate group of data analysts to draw insights from the varying datasets available to departments. The people filling these new roles are just as technically proficient as IT staff. They simply report to a different department.

These new application administrators and data analysts typically become part of the operations team within each department. However, in smaller groups, they could be a part-time job for a technically proficient marketing manager or sales representative. Regardless of the formal job title, someone has been tasked with managing the apps and data used in day-to-day business workflows. In 2024, that someone is rarely part of the IT team unless you're talking about a core business application.

The Automation Myth

It's these operations teams that are using Workato for their integration needs. That's particularly true when it comes to Generative AI workflows, the majority of which are owned by operations or applications teams. Workato would like people to believe that regular marketing or sales users routinely use their product to build complex automation workflows. That's simply not the case. For starters, 56% of Workato automations are owned by IT. Only 11% of their automations are owned by users outside of operations or technology roles, and many of those will be the aforementioned defacto ops guy historically guilty of creating Excel macros.

Enterprise technology is a complex beast, particularly once you consider the proliferation of niche services used by a single team for one task. It simply isn't possible for IT teams to understand and manage every application in modern enterprise tech stacks that contain hundreds of specialised systems. However, IT does still have a core responsibility to know where business information resides, how it is processed and whether it has been appropriately secured. This requires visibility of the entire tech stack, even if other teams are responsible for the actual configuration.

Maintaining Standards

Operations teams need to work closely with IT to ensure that security standards are enforced and that best practice information management processes are followed. An open and collaborative relationship between IT and the business is an essential ingredient for a healthy technology stack. Yet, I've worked with many operations teams who view IT with suspicion. Sometimes, that concern may be justified. Frequently, it is not.

The relationship between IT and operations typically boils down to the nature of collaboration between departments. If IT is seen merely as the people who say 'no', then they will be sidelined by the wider business. Instead, they need to be seen as the source of information standards and security best practices willing to offer constructive solutions to potential risks and inefficiencies. In an era of distributed application ownership, IT must become a coach for operations teams, who often overlook the dangers posed by applications in the rush to get things done.

No one expects everyone in the organisation to analyse large databases or engineer new services. Yet, every team needs access to those skills. The job descriptions and reporting lines are secondary and depend very much on organisation and cultural factors. Once in place, such individuals are responsible for delivering both business value and information security. Delivering both requires trade-offs, and identifying the right trade-offs is a separate skill in itself.

Banner Photo by Dom Fou / Unsplash

Written by
Marketing Operations Consultant and Solutions Architect at CRMT Digital specialising in marketing technology architecture. Advisor on marketing effectiveness and martech optimisation.