Why Manufacturers Need to Look at New Frontline Workforce and Enterprise Optimization Project Deployment Methodologies
The phrase “pilot purgatory” has become an infamous descriptor for many IoT, frontline workforce, and digitization projects, and it has been written about by virtually all top research and tech companies. The conjecture is that companies initiate and then get stuck in the pilot phase of their digitization, IoT, and optimization projects, which fail to scale and leave users, managers, the C-suite, and the shareholders frustrated. Different views have been presented on why projects get stuck in pilots and many theories have been presented to help companies avoid the pain of a stalled, slowed, or failed project.
LNS Research presents a unique perspective on pilot purgatory, claiming that companies do not necessarily get stuck; rather, they just haven’t planned ahead, and this is one of the major problems with most transformation projects. Most companies deploy only a partial functionality gamut of a platform across specific use cases to get a proof-of-concept. Then, based on the performance in said use case, they decide whether or not to scale the solution further. Another reason for slow post-pilot progress is the way such projects are driven and funded. Unlike the ERP (which most companies use) and other enterprise solutions, the external drive for digital transformation projects in manufacturing is not very high, and this can create funding hurdles, especially when projects are driven from the bottom up.
Figure 1, below, outlines the digital transformation project implementation strategy employed by companies, and it clarifies why most companies haven’t made headway in their digitization efforts beyond a point. As the data demonstrates, a very small number of companies deploy solutions across one or multiple plants for all functional areas, and value chain-wide deployments are even rarer. Being stuck in a pilot is bound to happen. Unless companies start using more top-driven and all-pervasive implementation and deployment strategies, results from transformation pilots will always be suboptimal.
Figure 1- Source: LNS Research
Traditional Development and Deployment Methods Are Broken:
Typically, when transformation projects are deployed, use cases across an operation are cherry-picked and detailed performance requirements are outlined. The deployed application or platform must deliver these requirements against the use case and in the given functional areas. In custom solutions, a waterfall method may be followed to create a tailored solution against the use case, which would then be designed, developed, tested, and released.
In this method, any changes made to the requirements as the solution is developed lead to delays. Even with the agile development methodologies used in modular applications and platforms, changes requested during deployment might lead to delays if they are frequent and require coding each time a change request is made. The major flaw in such deployments is not predominantly the way software is developed, although agile methodologies are preferred over the waterfall method. The major issue is the cherry-picking of use cases and the partial deployment across only a few selected functional areas. Now, let’s examine why.
Any transformation effort, even a pilot, requires change management and getting users on board to truly embrace the new initiative. When an application is deployed partially and covers only a few functional areas, it deprives users of detailed insight into what the solution can deliver on the whole. Furthermore, as the deployment progresses and changes are made, it becomes harder and harder to successfully quantify the ROI of the deployed partial solution. Over time, if the solution isn’t scaled, users will get frustrated with having to deal with multiple systems. As momentum is lost as a result of the change, the project may get stuck in pilot purgatory.
So, if the use case based partial deployment of transformational solutions doesn’t work, what does?
In digital transformation projects, especially those involving FLW, the goal has to be 100% employee engagement with the deployed solution and the use of a platform that is easy to configure, intuit, and deploy across the board. This is what the lighthouse deployment approach delivers, and it makes the lives of workers and management a lot better from a deployment, use, improvement, and ROI perspective.
The Lighthouse Deployment Approach:
The aim of FLW digitization projects is to empower workers with digital technology that helps them do their jobs better while also providing management with insights on overall performance from the shop floor and the extended operation. Webalo is a best-in-class digitization platform that digitizes all aspects of an FLW operation and helps enterprise optimization. We suggest the lighthouse deployment strategy for manufacturers instead of the traditional use case based deployment.
As the name suggests, the lighthouse approach encompasses a plant-wide deployment of the platform. Depending on the number of plants in a given group, deployment can happen in each geographical location or in one plant that serves as the model for the remaining ones in the group. This approach advocates for deployment that engages 100% of the workforce, and it happens when all functional areas are connected through a single solution and all workers engage with the same platform.
The platform allows for the creation of applications that digitize existing workflows and work instructions, replace all paper-based forms, and help collect previously lost process data from all functional areas. Figure 2 illustrates the lighthouse deployment strategy. This deployment approach emphasizes the rapid development and deployment of lighthouse apps. These apps aim for the creation of a Workforce Intelligence Center, the training of workers, and rapid adoption across the board and in all functional areas of an operation.
Figure 2- Source: Webalo Inc.
When an FLW platform is deployed using lighthouse methodology, all workers must engage with the platform. From a functional perspective, this means that the platform now orchestrates the entire process, from receiving raw material in the store to production, quality control, and the final warehousing and dispatch of finished goods. When this happens, workers are fully accustomed to the platform, and their ability to create their own apps on the mobile devices they are familiar with drives both adoption and improvements.
As one facility develops the full range of functional benefits and starts to show progress, the next stage of deployment can happen, which is rolling out lighthouse apps across other plants in the group and, if needed, generating additional apps. This is illustrated in Figure 3, below.
Figure 3- Source: Webalo Inc.
Plants that have used the lighthouse deployment model claim that they have experienced productivity gains of 5 to 10% in the first year and up to $1 million in annualized value creation per plant starting in the third year. They consider overall productivity gains to be around 20%. These numbers are a testament to the success of the lighthouse deployment model that comes highly recommended by Webalo project experts. The key to success in FLW projects is subjecting a plant to a solution for a sustained period of time and allowing users to leverage the entire functional gamut while making improvements themselves.