The role human workers play in automation
What if there’s a power cut? It seems like a silly question, but it’s a reflection of deeper issues surrounding the role human workers play in companies turning to automation
Often talk of automation is met with some sideways glances and whispers of jobs being made redundant. However, if the last few years have shown us anything, it is that someone needs to be there to fix the self-checkout in the local supermarket.
Essentially, automation helps to relieve the pressure on workers during a labour shortage or at peak times, or remove the need to manually perform repetitive jobs. This results in streamlined operations and enhanced efficiency, which helps generate more profit across the entire business.
The importance of automation has grown in the face of Brexit and coronavirus, both of which promise continued disruption, labour shortages and fluctuating consumer demand. This, coupled with changing customer expectations and a shift online, means chief information officers (CIOs) need to reassess their automation offering.
According to Kofax vice president of brand and corporate marketing John Lipsey: “As organisations continue to embrace digital workflow transformation, automation becomes increasingly important. In fact, full-scale end-to-end automation has become a matter of survival in the wake of the pandemic. More and more customers demand frictionless experiences and businesses that don’t provide them may not be able to survive.”
Despite mention of full-scale automation, this does not mean “no humans allowed”. In fact, automation technologies work best when used alongside humans and should be a key factor for CIOs during the implementation process.
“When applied smartly, technology can help provide relief for human workers by facilitating repetitive jobs. This can generate leeway and the potential for more throughput,” says ProGlove chief executive Andreas Koenig. “The main benefit of this is that workers can then focus on the tasks they do better than machines.”
However, when it comes to implementing automation, it’s crucial to know where it is going to be best placed. “CIOs need to keep in mind that automation has its limits,” says Koenig. “Some processes just cannot be automated for a number of reasons, including too many product variants during many manufacturing processes.”
For example, in the ecommerce market, which has seen tremendous growth even before the pandemic. “Increased ecommerce transactions impact the fulfilment process as they come with drastically different delivery times and formats that will need to be handled. One customer may order a toothbrush, another a TV set. These two orders cannot be delivered through the same lines,” says Koenig.
“Automation comes with a substantial investment, limited applications and is time consuming in the deployment process too. So it is absolutely critical to precisely identify the opportunities and benefits automation may or may not deliver. Prioritisation and knowledge of the restrictions of the technology to be deployed are also critical aspects for CIOs to consider.
“Aside from adequate talent, all this calls for thorough knowledge of the organisation and its processes. So it may make sense to build that talent internally. And even though it may sound trite, it is mandatory to provide guidance, proper change management and clear communication when introducing automation.”
Getting the foundations right
For Koenig, the key technologies to look out for are “optical character recognition, intelligent character recognition, natural language processing, robotic process automation, machine learning or deep learning”.
But don’t panic if you haven’t even thought twice about some of these technologies because the needs of each business will vary across industries. CIOs need to be mindful that there is not a tick-box list of automation technologies they need to have and, as Koenig points out, there is no silver bullet or a one-size-fits-all approach.
A major benefit of automation is the level of scalability it offers, therefore starting with the basics can help solidify a good foundation for further investment, as well as gradually introducing the workforce to new ways of operating.
“At the end of the day, organisational success depends on the support of the workforce. Support requires trust and trust is built on transparency or the democratisation of workflows to support workers,” says Koenig.
“It is paramount to identify the potential of the technology you are considering. Technology must help to design better workflows and provide relief for tedious, repetitive or mundane jobs. In short, it will need to serve human needs. So any decision to automate needs to be driven by and rely on valuable data.”
First comes data, then comes automation
If businesses are going to start somewhere, they should start with their data, says Koenig. “Businesses, even though they need to be compliant with privacy regulations, definitely need to work more with the data they capture. Data refinement is a key concern here. It is critical to invest in technology that goes beyond simply collecting information by contextualising it so you can deduct actionable insights,” he says.
At the core of automation technologies lies a vast amount of data, collected by internet of things devices. How well you can process all the data gathered will govern the quality of business insights that are generated.
According to Kofax and Qlik’s white paper Using data for insights is still critical for business operations: “As the world evolves and more operations continue to be digitalised, business insights from data continue to be one of the fastest and most effective ways to derive value, from short-term actions to long-term investments.” Once the data has been captured, “complexity and errors can be removed from this resource intensive, manual process through automation”.
Further benefits can be derived by leveraging automation to combine “business data with data from other disparate sources and channels – customer data, customer feedback, operational data and processing data – and provide simpler, smarter ways to visualise business intelligence”. But the real trick, according to Kofax and Qlik, “is taking all the data acquired through intelligent automation and turning it into actionable information”.
The white paper continues: “Most businesses have become adept at collecting lots of data. However, finding the most efficient and effective means of understanding and democratising the data, and using it to make informed business decisions, is more difficult for organisations.”
Creating more transparency around the availability of data and making it more accessible can help solve this. “Organisations and users need self-service, interactive web-based dashboards that provide process and business insight, without the need to involve IT to build new reports or adjust database queries. It’s key to create custom dashboards or modify existing ones, or to filter and aggregate data for displaying content in a variety of views,” it says.
COVID-19 has accelerated the use of automation within procurement and supply chains due to its potential for improved cost efficiency and productivity, according to GEP’s 2021 Supply Chain and Procurement Outlook Report. Automation will help streamline processes and allow smarter collaboration in core procurement and supply chain activities.
“Automation boosts output and affords employees more time to focus on strategic work, allowing companies to do more with less,” the report says. “Platforms with built-in forecasting and supply network capabilities will leverage artificial intelligence (AI), machine learning and robotic process automation to reduce their reliance on individual spreadsheets and boost shared, real-time data and demand models.”
In another white paper, Artificial intelligence and its impact on procurement and supply chain, GEP says: “Applying machine learning to the discovery of patterns in supply chain data – the painpoints and most crucial factors for smooth, successful management of a network – can be revolutionary.
“As the data is interrogated under constraint-based modelling, the machine can extract the most influential criteria that impact inventory, demand, production planning, risk and logistics management, and supply chain optimisation.”
Many of the insights generated may have not have been previously understood or even known due to the sheer volume of data available. Access to such insights enables smarter planning decisions and introduces new levels of network agility and responsiveness, helping businesses stay ahead of the curve.
Is AI a cure-all?
However, the GEP 2021 outlook report also emphasises that automation is not a panacea: “It must be coupled with human insight into category demand and the impact of a lingering recession, and continue to manage fluctuations in safety for employees and partner suppliers.
“In atypical situations, though, algorithms alone can fall short. Early on in the pandemic when customers were suddenly requesting toilet paper instead of LEGO, Amazon’s algorithms were perplexed. The situation demonstrates that bulk ordering and extreme demand surges need human intervention to revise fulfilment and inventory replenishment.
“Businesses that combine human adaptability with machine-learning models will better withstand the shock of unforeseen disruptions. Algorithms still need a daily real-world context.”
Likewise, when it comes to implementing AI, it helps to start small and specific. GEP suggests CIOs look to target specific problems. This allows teams to build confidence and by taking the time to understand where the biggest value can be extracted, and then delivering a shorter project with well-defined objectives, this acts as a good testing ground before expanding the AI reach.