Transforming fulfillment operations with automation

By Georgia Wilson

Business Chief speaks to supply chain experts to discuss the use of automation for fulfilment operations

“A global supply chain typically involves many partners that reside in different time zones, speak different languages and possess unique systems, documents and data standards. This complexity puts tremendous pressure on workers to standardise across the transaction by bringing together the data, synthesising and processing it according to mutually agreed upon terms and conditions,” comments Chris Huff, Chief Strategy Officer, Kofax as he reflects on the current landscape within supply chains.

“As one can imagine, this is a time-consuming manual process filled with the potential for error, re-work and compliance gaps. Intelligent automation transforms high-cost and people-intensive fulfilment operations into a highly efficient and automated state, by bringing together automation and artificially intelligent technologies. Intelligent automation is able to ingest high volumes of data from disparate systems and people, transforming unstructured data into standard and structured formats to automate the workflow.” 

Over the years, Huff has seen fulfilment operations evolve significantly, in particular “more software on fewer machines with even less people involved. Fulfilment centres today are technological marvels that primarily operate with a high degree of autonomy. A mainframe in the 1950s can essentially be held in the palm of your hand in 2020.

The power of mobile, internet, automation and artificial intelligence (AI) has transformed the supply chain industry.” Within the industry Huff has seen applications of “converging intelligent automation and AI to create platforms that can predict future inventory levels by assessing a myriad of environmental factors and initiating actions to preposition supplies in the right place at the right time.

In addition, intelligent automation and internet of things (IoT) are converging to speed up fulfilment processing times by collecting disparate data, making assessments and taking actions, and intelligent automation and mobile devices are converging to enabling real-time tracking to improve efficiency while increasing customer experience.”

Benefits of Automation

Huff explains that one of the most important benefits of automation is adding a tremendous amount of capacity without adding headcount. “Organisations are able to deploy capacity in two primary ways: one is to initiate unbudgeted revenue, lifting opportunities that would have otherwise required headcount.

The second is, organisations can aggressively advance their efficiency, arbitrage and cost take-out opportunities to improve margins and profitability.” In addition to this Huff also sees the potential to “increase compliance to 99.9%, improve processing times, reduce transaction costs and most importantly empower humans by providing a ‘digital assistant’ to perform the low-value transactional work.”

Agreeing with Huff, Mohammed Rehman, Programme Team Leader of Computing at Arden University comments that “Efficiency is the key benefit. Automating routine and menial tasks improves a company’s efficient use of time and money. It can also help to eliminate human error.” 

Challenges with Automation

However, with innovation comes challenges, Huff highlights that “the challenge with this technology is finding the right combinations to solve the higher-value supply chain issues that will result in true transformational value. Complex supply chain business problems typically require ingestion of data from many different sources, transformation of unstructured data, task automation and automated workflow. Best-in-breed intelligent automation platforms bring all of this together to automate complex fulfilment operations.”

Threat of Cybersecurity

In addition to the challenge of combining technology for optimum transformational value, both Huff and Rehman highlight cybersecurity as another core threat. “Globalisation has blurred geographic boundaries while at the same time increasing risk.” comments Huff. “Government and private sector consortiums will become increasingly important as we seek new standards and governance to make these consortiums work by building trust among strangers.” Agreeing with Huff, Rehman adds that “Robots can be hacked just like a computer.

As with any strategy around cybersecurity, it’s about embedding processes around authenticity of data, procedures around verification and handling of data, and ensuring that people are educated about the risks and follow institutional policies and procedures. Periodic review and testing is vital to ensure that systems are behaving as they should.”

What is the future of AI?

Looking to the future of automated fulfilment operations, Huff sees the adoption of the dynamic combination of AI, machine learning and natural language processing, taking further hold within the industry in order to automate the analysis of data.

“The lifeblood of a fulfilment centre is data. While automation can help move data through a process with minimal human intervention - in most instances - automation can’t read, interpret and draw insights from data. This requires AI through the likes of machine learning and natural language processing. As a result, companies need to do more than just automate workflow, they need to use AI to read data, interpret it and deliver insights to the business.

At Kofax our intelligent automation platform allows our customers to ingest structured and unstructured data, and use our embedded AI to read data to deliver insights to a business. In most cases, we have seen the application of intelligent automation shift workers from low-value ‘data collectors’ to higher value ‘data users’. In addition, workers are finding greater purpose in their work, improving a company’s recruitment and talent retention.”

Huff also reflects on the development of predictive modelling in the future. “Predictive modelling is already being used in pockets, but the technology and algorithms are proprietary in most instances. This makes it difficult for small and medium-sized enterprises (SMEs) to take advantage of the technology. More open source predictive models that allow SMEs to utilise them would go far in levelling the playing field so we can adopt, scale and innovate faster,” concludes Huff.


 By Georgia Wilson


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