How is an $8 billion warehouse and supply chain logistics firm deploying AI? At san Francisco-based Prologis, Chief Transformation Officer Lisa Vincent explains that coupling proprietary data with new AI tools is helping the company do things like decide whether to repair or replace a warehouse’s roof, predict customer buying behavior, and evaluate electric vehicle charting locations.
We connected with her in August to discuss her role, current priorities, and the challenges of making change happen within an established organization. Vincent was previously Senior Vice President for Operational Excellence at Prologis, and prior to that was a VP at the $15 billion healthcare system Atrium Health.
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Role
As the Chief Transformation Officer at Prologis, my role is focused on spearheading strategic initiatives aimed at driving digital transformation and leveraging data to optimize business processes.
I joined Prologis when we were just embarking on our operational excellence journey and was tasked with helping to get that off the ground. Now, operational excellence continues to be a cornerstone of my role, as well as diving deeper into all aspects of our business to identify key opportunities. As we continue to add new business verticals, such as our energy and mobility businesses, I help lead the integration of these business verticals into our core real estate platform.
Process
What is arguably most critical to my role is ensuring that I orient our leaders and people to work on the right things that will make the most impact. My approach to this starts with close and regular conversations with senior leaders at the company to understand what keeps them up at night, where they are facing the biggest roadblocks and where they want to be in five years. I’m responsible for synthesizing this information, identifying the right approach and rolling out data-driven and tech-enabled processes designed for solving and scaling.
Data-Driven Innovation
Data drives everything we do. Over the years, we have built a 100 percent cloud-based data warehouse. We curated and modeled it and made it easily accessible across the company through various platforms and SaaS solution…
Additionally, we have made significant strides in the past few years on the accuracy and reliability of our data, making our data-driven decisions with even higher levels of confidence. We have also designed our processes with protocols that ensure the right data is collected at the right time, while making it easy on our employees to do so.
Measurement
You cannot improve what you cannot measure. That philosophy is why we collect data across all areas of our business. Our robust data lake stores massive amounts of proprietary data which we leverage to predict trends and anticipate the future needs of our customers. These predictive analytics allow us to stay ahead of the curve in terms of market demands, innovations and operational challenges. Armed with that information, we can craft tech-enabled solutions and strategies that make our business better.
I work very closely with our Chief Technology Officer, Sineesh Keshav, to identify ways AI can and should be deployed to help keep us ahead of what’s next.
Priorities
On top of nearly everyone’s minds is AI. AI is not new to Prologis; in fact, we have been using traditional AI/machine learning throughout our business for over five years. Our robust and scalable data foundation empowers our teams to leverage AI in a growing number of ways, including to enhance business decision making, achieve operational efficiencies and innovate customer solutions. I work very closely with our Chief Technology Officer, Sineesh Keshav, to identify ways AI can and should be deployed to help keep us ahead of what’s next.
What sets us apart is that we are not using generalized models. Instead, our proprietary data lake fuels specialized AI solutions. Some examples include our roof repair or replace model, which helps inform our capital expenditures around roof maintenance; our generative site modeling and design platform TestFit; customer propensity models to help predict customer buying behavior for our Essentials business; site digitization, automation and robotics; and evaluating electric vehicle charging locations by considering a myriad of data from power grid capacity availability and economic viability. The list is quickly growing.
AI Democratization
We are also committed to putting AI in the palms of all of our employees’ hands to help them do better business and be more efficient. We recently introduced our second-generation ChatGPT Enterprise, PLD GPT 2.0, which is embedded with our proprietary data and expertise and designed to help to speed up our ability to make good, data-driven decisions. (See below for a screenshot from Prologis’ internal ChatGPT platform.)
To support our people through our digital and data transformations, we are integrating more educational opportunities into our Learning and Development program, such as training programs to build data literacy. Staying focused on upskilling our employees and encouraging them to be curious ensures no one is left behind.
Challenges
Enabling any sort of business transformation requires strategic change management. Change management is not easy, especially when things – such as the capabilities of technology – are evolving so rapidly. Human beings are creatures of habit, so they can be resistant to change. As we focus on organizational effectiveness, productivity and cost reduction, our experience has taught us that we must include the “human side” of change if we want to achieve real change and ROI. The fact is, there is no improvement unless people understand what is in it for them and shift their behavior to utilize the new process or system as intended on a sustained basis.
…There is no improvement unless people understand what is in it for them and shift their behavior…
With our global scale, data collection is massive. The data we collect from our customers alone – all 6,700 of them – may be a year’s worth of data at a time. For example, our property managers pull a year’s worth of utility bills from our customers so we can better understand how to deploy solutions that bring their energy usage and costs down. As you can imagine, collecting and reviewing this data takes a substantial amount of time. And, this data is coming in from all over the world. What used to take weeks and hundreds of people now takes a small, dedicated team a few days through process and technology improvements.
Governance
We are laser-focused on data accuracy and security. Historically, we had no controls or process for vetting new data fields that we are asking field teams to collect, which can lead to systems and data fields growing without a cohesive intent or strategy behind them. That is why we established our Data Governance Committee to vet data requests for alignment and ROI. The committee reviews any addition or removal of data fields to ensure a cohesive, centralized strategy.
