By Jeremiah Seraphine, senior consultant and entrepreneur in residence

Legacy automakers are deep in the throes of a once-in-a-lifetime transformation into software-led electric vehicle manufacturers. To successfully make this change, automotive software teams have a challenging task: accelerate their transition to a modern software development organization and improve software quality – all while continuing to deliver products with unimaginable complexity at the blazing speed of manufacturing.

Software teams are often facing these challenges with fewer resources as automakers work to cut costs. And to complicate matters further, we are seeing more software re-organizations that are putting even more stress on internal data systems and forcing teams to adjust to new ways of working.

In our work with legacy automakers, we’ve encountered three business operations “anti-patterns” that significantly inhibit strategic initiatives:

• Inefficient collaboration and information sharing
• Qualitative management blind spots
• Resistance to automation

It is crucial that automakers systematically address these anti- to leap ahead of the competition.

Inefficient collaboration and information sharing practices

We’ve seen this anti-pattern at many large companies. In May 2023, the Wall Street Journal reported that “workers now spend two full days a week on email and in meetings.”  Some skeptics wave their hand at this metric, saying “This is simply how work gets done.”

However, researchers at the Georgia Institute of Technology in Atlanta found that it took 30% of the programmers they studied 30 minutes or more to resume work after an interruption. Software engineers clearly add value by writing code, not by attending meetings.

We often see meetings that are back-to-back and massively oversubscribed. In a typical meeting, a few active participants speak while scores of passive listeners lurk in the background.

Coupled with near constant manual reporting, and informal work-around processes, inefficient collaboration burns thousands of dollars and creates a blackhole-like gravitational pull on the organization’s most precious resource: employee time.

Qualitative management blind spots

In a large software organization, leaders are rarely the first to know when a project or team is beginning to go offtrack. That early signal first emerges within the teams closest to the problem and is often understood qualitatively before any quantitative measures pick it up. As that information makes its way up through the management layers of an organization it is subject to unconscious bias and/or conscious political spin. This keeps leaders at the top from knowing the ugly truth until it finally spills onto their dashboards or gains enough widespread understanding that it bubbles up from multiple sources.

Systemic team disfunction is not only a threat to quality and productivity – it also threatens companies’ ability to retain talented team members.  However, most leaders do not have good ways to get unbiased, qualitative signals quickly, consistently, and at scale.

The organizational scale of legacy automakers and the daily demands of software leadership can make it difficult to systematically and consistently gather this intelligence.

Holding skip-level meetings, with fact-finding interviews, project deep-dive reviews, and anonymous work networks, can be a valuable tool to uncover some of these qualitative issues.

Resistance to automation

All organizations say they aspire to automate manual processes around coordination, collaboration, and communication, but in practice it is extremely difficult to achieve.  Automations that would make big impacts often span multiple siloed teams within an organization and take considerable leadership support to overcome resistance. The tendency for over-compartmentalization of information further prevents these efforts from ever gaining real momentum.

Take management approvals for instance. These efforts can be painfully manual and waste hundreds of hours over multiple management levels each month. Automation can create impactful efficiency gains when implemented at scale. However, leaders must buy in to process changes, and this often requires time, political maneuvering and cross-organizational coordination.

The opportunity to address these anti-patterns

These anti-patterns are very common in large enterprises, and lacking easy-to-implement solutions, have historically been difficult to address. However, the advent of enterprise AI is rapidly changing this. We see these trends emerging:

• Increase in smaller, high performing teams working remote/hybrid
• Automation to remove most team overhead
• Increases in asynchronous collaboration to free up deep work time and increase productivity
• Qualitative insights from unstructured organization data

Increasingly, small teams operating with smarter systems will outperform larger enterprises. Effectively optimizing collaboration and sharing practices, addressing qualitative blind spots, and overcoming the resistance to automation is happening across the business world at an increasing pace. The enterprises that embrace this change will gain a head start over their competition.

The winners will embrace the new way of collaborating, using remote and hybrid work as a competitive advantage. New AI-powered systems will help small teams stay in sync without the need for redundant meetings, constant human-generated status reports, and people acting as inefficient conduits between incompatible systems.

Leaders who embrace this new way of working and strive for organizational transparency over unnecessary secrecy will be rewarded with a new class of insights. Leaders will finally get a full picture of what is happening in their organizations and get early signs of changing dynamics.

And the others will be stuck in a pattern of anti-patterns.

Jeremiah Seraphine is a co-founder of Empwr.ai , an Envorso incubated Software as a Service (SaaS) solution that unlocks productivity for teams by transforming conversations into action and collective knowledge.