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Are you ready for an AI-enabled Transformation?

Posted by Julia Walsh on Jul 7, 2022 7:22:21 AM

Understanding the role, a connected enterprise and an empowered workforce plays in laying the foundation for a successful AI implementation.

A common misconception when it comes to Digital Transformation and Industry 4.0 is that with the rapid adoption of the technology gamut associated with them, the manufacturing operation would, as a step change, transform into a fully automated endeavor, orchestrated almost entirely by autonomous AI applications, self-optimizing and self-driven.

The reality, however, is far from it. Manufacturers need to understand and appreciate that Industry 4.0 and the digital transformation which enables it are meant to improve the current ways of doing things, and essentially, they target the same deliverables as before, cost, efficiency, and profitability, however, with process data, AI and other tools added, to deliver results faster and to make the operation more agile and resilient, which in turn helps cope with and over time leverage market uncertainties.

Now, AI is certainly a big and vital part of digital transformation, however, in order for AI to successfully deliver what it is capable of, certain underlining factors need to exist in a given operation. AI as a tool is meant to replicate human intelligence, when applied in the context of manufacturing this implies the ability to either augment or automate decision-making related to tasks and activities, which when performed in the requisite sequence create and punctuate the manufacturing process. AI would not succeed unless it is deployed in an operation ready to leverage the benefits it brings and to be ready isn’t necessarily a plug-and-play option, it requires diligent work and the right IT infrastructure!

For AI to unravel and really add value to the operation it needs copious amounts of standardized, well-formatted data, through applications that can then take the intelligence created and enable workers to create value through well-informed and faster-than-before actions. Most organizations, however, do not have this ‘data’ ready nor the application infrastructure needed for AI to succeed, as PWC points out in a report, there are six main factors that lay the foundation of a successful AI implementation in any organization, the top two are, Business Applications and Data.

Let us fully understand the gravity of why we have chosen these two factors as the ones most relevant for manufacturers for our post. Business applications, provide the necessary foundation for any successful AI implementation, by providing an ecosystem that not only provides raw data, but also provides connectivity, standardization, and structure. Data itself is the key to digital transformation and dark data is a real challenge even in most modern manufacturing plants, with IoT-enabled devices and sensors. Manufacturers need to figure out how they can bridge the gap which exists between their enterprise (ERP, WMS, CRM, MES) and their shop-floor while digitizing and empowering their frontline through the lifeblood of any digital transformation endeavor, data, and IT platforms.

Connected Workforce and Integrated Enterprise:

First, let’s focus on business applications, now, most manufacturers employ workers to execute production activities, however, with the way in which their IT infrastructure has developed over time, the frontline workforce is the most neglected when it comes to connectivity with the enterprise and digital tools which enable this integration.

Knowledge workers, managers, supervisors, and support staff typically have applications that enable them to make more informed decisions and connect them to other parts of the operation, however, where the frontline workforce is concerned, very few organizations have begun the digitization of the manufacturing process. Without a connected frontline, the basic platform required for AI to succeed is missing.

TechRepublic points out that employees can achieve a whopping 37% more in terms of productivity when using the ‘right’ technology and tools, conversely, bad technology reduces productivity by 30% and the stress it leaves carries on with the workforce beyond their working hours. What this means from an AI and Digital Transformation perspective for manufacturers is two things, one, having the right IT platform to connect and empower workers is extremely important for a higher degree of success, and two, neglecting the manufacturing operation, which creates the largest amount of decision rich data might be a major error, when planning the overall transformation strategy.

Manufacturers need to look at the numbers from TechRepublic and re-evaluate how their workforce currently operates, are they still using paper-based forms, and do they still need to enter manufacturing-related data from a work-station or desktop? Is the shop-floor operation governed through a single platform? Are the applications used by the frontline enabling them to work faster, making them more mobile, or adding to their work woes?

Unless you have an IT infrastructure that empowers your frontline while connecting them to the enterprise you are not fully ready to reap the benefits a large scale AI implementation can bring!

The role of Manufacturing Data:    

IBM recently explained how dark data is created and why it is important to take notice of it. Data that is being generated in a high volume, without proper ways of maintaining and retrieving electronic records, might end up becoming dark data, another reason for the creation of dark data is the sheer variety of data that exists, siloed and unstructured data from myriad sources has a tendency to get lost, finally, the velocity of data creation at times leads to its loss, the ability of processing data simply does not match the speed of its creation.

In a typical manufacturing operation, it is a given that there might be multiple applications on the shop-floor, legacy applications that perform a specific operation/function, equipment-specific automation applications, and paper or spreadsheet-based forms that require manual updating to capture and report process data. Unless all this data being generated with every single transaction that happens on the shop floor is captured on a single platform and converted to standardized data which can then be used for analysis, chances are there is massive amount of dark data on this particular shop floor, which will never see the light of day.

Another set of interesting facts from an IBM study reveals that almost 90% of sensor data generated by sensors is never utilized and about 60% of data generated loses its value in milliseconds. As we established earlier unless AI engines have the right amount and quality of data their implementation will only yield sub-optimal results.

For manufacturers who haven’t yet embarked fully on their digital transformation journey, there are pertinent questions to be asked where shop-floor data is concerned. Are we capturing our process data? Is the data capture fully or even semi-automated? Have we successfully eliminated manual data entry? What is the current lag which exists between data generation, data capture and data reporting?

The Solution: Workforce Digitization Platform

Webalo, is a platform that digitizes the frontline workforce’s tasks and activities and provides the basic foundation upon which a successful AI implementation can be delivered, let’s understand how.

At its core, Webalo is a no-code platform that allows frontline workers, supervisors, and managers to build their own apps to execute and better manage their tasks and when applied as a lighthouse solution across the entire manufacturing and distribution process, it integrates the shop-floor to the enterprise, as a single overarching platform. When this happens, data is captured and reported in a more accurate manner and it is prevented from going dark. Since it is a mobile solution, it eliminates the lag which exists between an event happening and data pertaining to said event being reported, analyzed, and actions taken.

As a platform, Webalo addresses both top concerns raised by PWC pertaining to the successful implementation of AI, it forms the foundation for AI by allowing integration amongst shop-floor applications, point solutions, and enterprise-level applications and provides data in a standard, usable format while protecting meta-data.

Most importantly and to bolster the argument made by TechRepublic, it acts as a worker-friendly platform that helps frontline workers do their jobs better, which translates to higher productivity and better actions even before any AI-related project is even kicked off. However, when AI does eventually roll out, with Webalo, you already have an integrated application environment, coupled with empowered workers who not only know the importance of process data but are able to capture, report, and utilize this data better than ever before, all this would help any AI implementation succeed. So, if you are looking to speed up your transformation efforts, look first at your frontline and whether or not your process is ready to handle AI and all the challenges it brings, think optimization first, think Webalo!

Tags: frontline workforce, digital transformation, Industry 4.0, process optimization