SME & Automation
Small and Medium Scale Enterprises (SME) are the backbone of developed and developing economies. SMEs make a staggering 99% of the total industries in the US and 95% of the total industrial units in India. Nearly 28 million American SMEs account for two-thirds of net new private-sector jobs in the US [source]. And depending on the country, around 50–90% of the labor force works for SMEs [source]. Yet SME contribution to the GDP in the US is constantly shrinking from 50.5% in 1990 to 44.6% in 2010. In India, SMEs account for just 45% of the total manufacturing outcome and a mere 6.11% contribution to the GDP while employing 40% of the Indian workforce, next only to the agriculture sector [source].
The massive gap between the percentage of the labor force employed by the SMEs and contribution towards the GDP can be attributed to the low productivity levels of the SMEs. Within the same sector or countries with a similar size, the productivity gap between SMEs and large companies can vary by a factor of two or more. The key reasons for low SME productivity are their limited capabilities and access to resources. With industries focusing on AI and automation to increase the productivity and output of their existing labor force, there are currently 2.4 million robots operating globally in factories. Allowing humans to focus on value add & cognitive tasks while automating the non-value & repetitive tasks. But again, only 8% of the US companies have already implemented robotics systems [souce].
Governments around the world are setting up specialized departments to support SMEs and help them adopt new technologies. For example, the Indian government has an entire ministry (Ministry of Micro, Small, and Medium Enterprises) dedicated to SMEs. They provide access to capital and training towards the Internet of Things (IoT), machine learning, and AI [source]. But the challenge is not just with the access of knowledge but access to those “things” or tools where the IoT or AI solutions can be deployed.
Time, Cost, and Talent
In a survey conducted in 2018 by McKinsey, costs, lack of experience with automation, and lack of homogeneous programming platforms were cited as the top challenges for customers looking to automate. The long payback period of existing automation solutions is the biggest barrier to the adoption of automation. Existing solutions can take anywhere between 6–12 months to deploy, with almost 70% of the project cost going towards integration and deployment rather than the robotics hardware. Even after the deployment, there’s a need for specialized training or a skilled individual (graduate-level engineer) to ensure the solution works perfectly with time [source].
For SMEs experimenting with automation for the first time, asking for an upfront investment with a long payback period is a big ask. More than just the cost, the ask of having specialized engineers in the field is even more challenging. By 2030, it is estimated that US manufacturing will have 2.1 million jobs unfilled, with the strongest demand for technological skills [source]. The challenge of attracting and retaining specialized engineers in this competitive market is daunting.
The need for specialized training or software engineers also makes these robots seem like external devices that are foreign and scary to the existing labor force. So even if an SME successfully pilots a solution in a constraint environment, scaling them is another beast. To break Time, Cost, and Talent barriers, we need to focus on more than just upskilling and early financial support. We need to change the way we build these solutions.
Empowering Humans
The journey of computing from a select few engineers to a regular person can teach us a lot. The lowering cost coupled with the graphical user interface made computing simple for the everyday person and drove the expansion. Robotics is at a similar phase. The focus should be on building solutions that are intuitive for people on the shop floor and warehouses. We need new tools for the new era of industrialization, not machines that scare people working with them.
Collaborative robots (cobots) are already paving the way. While closing the skill gap, cobots are working next to humans adding value to everyday operations. By reducing the integration and deployment times, cobots are providing flexible solutions while demanding lesser infrastructure change. No-code deployments are the next frontier making an everyday person a robotics engineer with minimal training.
The collaborative and intuitive systems will allow us to break the time and talent barriers but it’s also essential to remove the cost barrier by providing SME-friendly payment terms. Where Robot As A Service (RAAS) is a great way to start, leasing machinery for the long-term is not a preferred solution for industries. Probably a mix of RAAS and CAPEX can be a way forward. SMEs can work with the robots, understand the value-add while being on a leasing period and buy the robots if their expectations are met. The path towards bringing automation to the SMEs is not via large, high budget, and grandiose projects but by incorporating humble low-scale deployments that can scale with time.
At Peer Robotics, we are building the next generation of collaborative mobile robots, allowing material handlers and operators to deploy the mobile robots using our feedback-based learning algorithms. To learn more, please connect with us at Peer Robotics.
