Q&A With Heidelberg Materials’ Erica Flukinger
Different applications of Artificial intelligence (AI) are everywhere these days, and the concrete and ready-mix industry is no exception. However, as an industry in general, it tends to be more pragmatic and more skeptical about adopting newer technologies than other industries. So, how can ready-mix companies explore AI and implement these technologies into their company practices in a smart and responsible way?
One of the best resources for learning about this type of technology is through trusted and customer-centric software companies, according to Erica Flukinger, Digital Director of Heidelberg Materials North America.
“Ask to see where and how they have the vision to embed AI into their business process software,” Flukinger says. “Ask specific questions – even use generative AI to help you come up with those pointed questions – and ask them to get clear on what exact kind of AI is doing what inside the software. AI is a large umbrella term so don’t fall for hype or hazy claims.”
Flukinger also encouraged people and companies to do their own education and research and see how other industries started on this AI journey years ago. “We have the benefit of sometimes being later adopters so we can catch up on other industries’ shoulders and learnings,” she said. “Get informed, get interested, and as Matt Jetmore from Lauren Concrete advised and repeated at an AI panel at TACA’s Annual Meeting last year, ‘Pay Attention.’”
BCMI, developer of cloud-native dispatch, performance analytics, interactive communication tools and AI-assisted solutions, was a part of this panel discussion on AI in our industry as well and wanted to dive deeper into Flukinger’s interest in AI and how Heidelberg Materials, a leading supplier of cement, aggregates, ready mixed concrete, and asphalt, is incorporating it into their own processes and procedures.
Q: How can producers find efficiencies with AI? What are some easy ways they can incorporate AI into their businesses?
EF: It makes me very excited for AI to become an observer, scribe and recorder of institutional knowledge and then the trainer, support and practical “walking stick” to the next round of people entering key jobs. We don’t train enough in this industry. And what do the best athletes in the world do? They train. The best teams? They train. AI can become a true on-the-job trainer and onboarding tool that this industry could never imagine and I’m excited for some companies to tap into that power and invest there because it will pay for itself in speed to reach full productivity and reducing risk of errors and knowledge gaps.
Q: Any areas where integrating AI makes the most sense? Or where implementing AI is easier?
EF: There are large areas of the logistical and production-centric businesses where AI might be considered depending on your goals and challenges. Areas like inventory management, route optimization, demand forecasting, predictive maintenance and safety.
Easy is a relative term, but there will be quicker uptake for use cases of generative AI, which could apply to any job tasks that require the creation of content. This is where generative AI might seem like a quick win. If you need to write job postings that people want to read, analyze information, make the structure for a project plan, draft social media posts, brainstorm ideas, summarize information, and design meetings and agendas. There is an energy tax to the creation of content and generative AI can short circuit the natural procrastination or energy barrier we can sometimes feel on busy days and hectic weeks to get started on making a first draft, or give us a 60% starting point to a customer letter, proposal document, checklist for maintenance procedure or anything else that requires critical thinking and uninterrupted concertation time as specialists or business leaders.
Q: How has your company implemented AI?
EF: We are a large, multinational company, so there are numerous pockets of experimentation and success depending on where you zoom in. Some of my favorite examples include how technology can observe ready-mix concrete truck-driver fatigue and help coach “in the moment” with no shame to the driver and no extra effort to our supervisors to “catch” or correct “bad” behavior, but more real-time, facts-based, prompts to ensure drivers are alert and undistracted. It even helps to teach and train when there are persistent, higher risk habits a new driver might show like lane departures or following too close. This is the same kind of technology found in your doorbell cameras telling you when a package is delivered or car insurance companies monitoring your driving behavior to help give you lower rates for good, consistent driving behavior. We accept this kind of technology in our personal lives and must learn to embrace it as openly in professional settings too to bring benefits to each kind of employee who works for us. They all want to do a good job, and having technology compliment them is something they will all embrace if you take the time to personalize what benefit they each receive in return.
Q: Was incorporating these new technologies within your company challenging? Were there concerns within the company? If so, how do you overcome those?
EF: Any new technology will bring known and unknown challenges but equal excitement and energy. And that mix will differ depending on your level and role in the organization. What is universal, however, is an organization’s ability to evolve. If organizations historically stay stagnant, try to continually self-preserve, and stick to status quo ways of thinking and operating, they will struggle at every phase of the game to be open to continuous improvement, adopt new technologies, and unlock the financial or operational benefits.
Probably the main hurdles would include a couple of consistent themes. First, do you truly understand what problems you want to solve first and what is at the root of those problems before even jumping to technology being an answer or part of the solution? Second, are you prepared to adjust your processes in new or different ways vs. bending the technology to your current processes and roles? How open are you to having your business operate differently with a different organizational chart, new or different kinds of roles, different and unique skills, and backgrounds? This doesn’t mean you have to completely gut your house, but are you willing to work with your existing team to remodel and update the parts of your house that need to be modernized and increase the value of the home, business, and honestly, productivity and enjoyment to “live” in that business/home to keep the metaphor going. We work in construction so we know how challenging any project is but that also gives us a leg up to have the resilience and tenacity to see it through and enjoy the benefits on the other side. Even though we are discussing the future, a lesson from the past still rings true from Charles Darwin. “It is not the strongest nor the most intelligent of species that survives, but the one that is most adaptable to change.”
Q: Where do you see AI technology in five years – and how will it specifically impact materials producers?
EF: Pattern recognition and prediction. Today we see the unpredictable factors of weather, market conditions, and staffing as beyond our control. But what if we can start to see and predict patterns that drive improved and proactive decision-making? Things related to project schedules, customer behavior, maintenance needs, predictive turnover risks, or other persistent challenges that zap manager’s focus and attention. What if we can start to foresee those problems more proactively with a super brain that is helping to confirm your intuitions and decades of experience?
Also makes me excited for how we could see some jobs shift because we have conditioned the customer to perform tasks for themselves drip by drip. Confirming orders, placing orders, changing orders, all based on a historical model. Thus, building out a schedule for the day based on plant, truck, material and employee availability. Even when changes or cancellations are coming in, the model is adjusting itself, learning and relearning. Will we have a world one day where customers “dispatch” themselves? Where availability and consistency can be even more consistently achieved for our customers’ projects and plants as we act like a more interconnected network of suppliers and resilience of our industry. Of course, we’d have some guardrails, but this could be possible and sooner than we might think. It’s all about keeping our businesses personal and customer-service orientated with the right level of technical enablement in the mix
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