There was a real sense of excitement and urgency among the exhibitors, sponsors, speakers and attendees who gathered for the Autonomous Mobile Robots (AMR) and Logistics Conference in downtown Memphis this month. The strapline for the three-day event – ‘it’s time to get moving’ – summed up the mood of an industry that’s restless for action as the pandemic recedes. But make no mistake, tough challenges await both the big industry players and the new wave of start-ups with ambitions in the space.

Automation to autonomy: navigating the path to success

As a speaker and panelist, I was honored to take part in a lively debate on the subject of choosing the right technology for warehouse automation. In this article, I plan to reflect some of the insights from that discussion – and also share my views on how industry innovators can best put a strategy together to turn automation challenges into opportunity. But let’s start with some scene setting, to give you more perspective on the mindsets and attitudes characterizing the AMR and logistics community right now. 

FedEx, the Memphis-based global transportation and technology leader, was official title sponsor for the conference, which was attended mainly by technology solution providers for warehouses, fulfilment centers, and those concerned with material handling automation. There was a great mix of start-up innovators along with big established players all looking to move up the technology capability curve.

The big picture is clearly dominated by the business effects of the pandemic. The significant acceleration of ecommerce and resulting demands from consumers for rapid service has put huge pressure on the delivery side. This weight of expectation on logistics has been heightened by the severe labor shortage.

Perfect storm of high demand and short supply 

During one of the panel conversations, the Korn Ferry report was referenced that predicts a global human talent shortage of 85 million people by 2030 – which left unchecked could result in $8.5 trillion in unrealized annual revenues. There has always been a problem with staff turnover on the service industry side, but with the current perfect storm of high demand and short supply, there is a gaping chasm right now that needs to be filled by automation. 

The traditional material handling systems are not architected to address current needs in operations and logistics. And on the other side of the coin, the innovators and start-ups have their own problems when it comes to rising to the rapidly changing market needs. They might have a solution that works in the lab, but it has not yet necessarily reached a maturity that make it ready for deployment for large users like Walmart, FedEx and others. While its future is promising, it’s not yet ready for scale; it’s not designed to operate seamlessly with other technologies in the warehouse. And, while progress in functionality is pretty impressive, it is nowhere near to being what it needs to be – a mission-critical application with functional safety, robustness and reliability. 

In my view, the situation can be boiled down to three essential tasks, the first being to continue their experimentation cycle to advance their capability. The second is scalability, which means elevating their strategy to a system thinking approach with the necessary product development processes. The final one is convergence and interoperability – these innovative systems must work with existing systems and with each-other.

We spend a lot of time here at CC advising clients on the crucial issues of scale up, flexibility and reliability. We urge them to not focus only on technology, but rather deliberate on how to deploy technology at scale within their operations. This means that one of the first areas we help with is to determine desired theoretical system capability driven by end-user economical value. We advise our clients to utilize simulation end-to-end: from simple mathematical modelling of KPIs and the verification of early architecture assumptions to full level system level simulation application.

Developing an autonomous system that can reliably operate (that is navigate and articulate actions) under various operating environments is hard to build with only limited real-world data. Moreover, it can take decades of usage in different environments to prove reliability and/or functional safety based on real- world data. We need to augment finite real-world data with synthetic data and simulation capabilities to be able to build a reliable system that performs under various workloads and navigation needs – and establish a safe working environment in warehouses. We can help build the automation system in simulation mode to be able to meet diverse operational, reliability and functional safety needs.

The KPIs needed to drive automation 

Another important area to focus on is the modelling piece, which needs to be addressed well before defining the automation system. It’s vital to connect your business strategy, operations and automation systems. It means establishing your business scenarios, KPIs, operational needs and relevant process flow models for your operations. This will enable you to define your automation system requirements in terms of functionality, performance, utilization and safety.

The automation to autonomy journey

The panel was asked about it views of how best to apply a strategy of ‘crawl, walk, run’. ‘The Goal’ – the book by Eliyahu M. Goldratt – was quoted in the context of strategic operations planning. I agree on this vital point. It should never be a case of automation for the sake of automation or tech improvement for the sake of tech. The smart thing to do is to step back and work out the goals and bottlenecks, before looking at the technology as the solution. So, when it comes to ‘crawl, walk, run’, the answer is to think big and look at the goals before designing the right proof of concept and pilots with a good scale-up strategy in mind.

We had an exciting discussion on the merits of future-proofing. On one hand, rapid technology development makes future-proofing almost impossible and end users may need to adopt an iPhone/PC user model for warehouse technology, with new features and new capabilities coming on stream year after year. On the other hand, this is capital equipment and significant undertaking, so some future-proofing in terms of anticipating future demand and the ‘jobs to be done’ framework by Clayton Christensen is absolutely necessary.

I take the latter position. End users spend multi-millions of dollars on warehouse automation projects that will take years to return profit. They also invest time and resources in verifying, validating, launching and deploying – and even the most benign changes need a full circle in that process. And, while as technology developer, I’m eager to see the latest tech on the hands of users, this is mission-critical capital equipment and its update is harder and bears significant cost.

There were plenty more fascinating themes under debate during the conference, which I plan to return to in future blogs. The idea of XaaS – in this case robotics or automation as a service – is an interesting area that I want to explore in more detail soon. We’ve already worked with a couple of major clients like Ocado who have developed their own warehouse automation and license this technology as a service to other grocery retailers globally. There are lots of talking points here that will be of interest to a number of industries beyond the warehouse and logistics sector. So, watch this space – and meanwhile please drop me an email if you’d like to talk about any of these topics in more detail.

Author
Oli Qirko
President, North America, Cambridge Consultants

Oli has 20 years’ experience of helping leading global corporations to develop breakthrough products and services in a range of markets – from consumer and industrial to logistics and transportation. At Cambridge Consultants, she now partners with Fortune 100 and start-up companies to launch digital transformation and automation initiatives. These leverage global organization capabilities in AI, advanced sensing, robotics and wireless communication. Oli holds a master’s in electrical engineering from WPI and an MBA from MIT. As well as serving on the WPI Engineering Advisory Board, Oli lectures at MIT Sloan School of Management. There, she mentors CXOs and executives on how to manage the most critical and complex organizational challenges in business, technology and global operations.

 

 

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