— Read Time: 4 Minutes 30 seconds–
When manufacturing companies embark on their digital transformation journey, they come to the marketplace with real needs. Despite their best efforts to implement traditional reactive or preventive maintenance, their operations are still plagued by random machine failures and costly unplanned downtime events. The first logical step toward digital transformation—and avoiding these problems altogether—is to optimize asset management by digitizing machine health. This is because machine health is the heart of industrial digitization.
Within a manufacturing company, in order to set digital transformation strategy up for success, it’s critical to have a formal evaluation process for new technologies. This evaluation process will help you select the right technology partner to reduce maintenance cost and unplanned downtime, leading to higher throughput, better profit margins, reduced risk and reduced stress for maintenance teams.
Each organization approaches evaluating digital technologies in different, but similar ways. Some approach this by developing a group of internal experts to leverage as consultants, some from a top-down methodology, and some from a bottom-up methodology. Below, we’ll explore these three common approaches to digital transformation strategy and the high-level impacts of each from a machine health monitoring/predictive maintenance (PdM) perspective:
Approach 1: Create an Innovation Group
This approach treats digital transformation as an experimental process where many types of technologies are evaluated by an internal coordinated group of experts. These companies typically adopt PdM in small, tightly controlled pilots, which focus on a number of “bad actor” machines that cause the entire organization problems.
Working towards scalability, the innovation group typically runs quick pilots that take 6 months or less. During the pilot period, the innovation group gathers data to report back to decision-makers with recommendations regarding if and how to scale the technology. Generally, these groups do not control budgets; they act as internal consultants who evaluate technologies against a predefined set of criteria and report back to decision-makers.
The innovation group approach to digital transformation can be slower than other approaches because the group evaluating each technology often won’t make the final call on implementation. Their recommendations, even ones that point to quick action, may not be adopted with urgency, if at all.
Corporate culture can be the key differentiator in the innovation group approach. A company that prioritizes and empowers innovation may give the innovation group more authority. These companies are more likely to put systems in place to support adoption through quick decision-making and appropriate budget allocation.
For example, a facility management company that Augury works with placed innovation at the forefront of their corporate mandate, making it their key market differentiation through automation.
As a result, they created an innovation group with broad organizational access and significant decision-making authority. The group included a dedicated Project Manager who worked closely with Augury to track and quantify savings. This group quickly discovered strong ROI results and communicated their findings across the organization. The innovation group subsequently received approval to scale the solution rapidly.
Approach 2: Digitize the Supply Chain
In this approach, companies tend to prioritize efficiency in the supply chain and take a macro approach to a successful digital transformation strategy. Their internal digital transformation teams are typically led by operations executives with a broad focus on high-level operational KPIs across several areas of the supply chain, including transportation, logistics, sourcing, and go-to-market strategies. These executives generally control a healthy budget that can be leveraged to create efficiencies through digitalization.
These companies tend to favor solutions where a single platform can visualize all necessary data–creating informational efficiency as well as operational efficiency. This, however, is difficult to achieve and most discover that not all data can be combined in one single “source of truth.”
Another common issue is that supply chain professionals are typically not reliability or manufacturing experts and are not used to analyzing detailed mechanical data or diagnosing machine malfunctions. In these cases, including a reliability engineer on the assessment team can help improve project outcomes by providing insights from a subject matter expert.
This top-down approach benefits from ease of adoption because supply chain efficiency is considered an organizational priority. When teams have decision-making power, budget, and motivation — it tends to lead to a faster return on investment. However, to ensure successful digital supply chain expansion, it is critical to receive plant buy-in in addition to corporate support.
Approach 3: Start with the Shop Floor
In this approach, companies take the experts-first approach to digital transformation by allowing reliability engineers and maintenance teams to be the first evaluators of the system and weigh its pros and cons.
The key benefit here is that reliability leaders and field reliability engineers have intimate knowledge of mechanical data and site processes; they quickly understand the value drivers of machine health monitoring solutions. They also typically have the authority to launch pilots on various sites and can easily identify the benefits and barriers to implementation.
The main drawback, however, is that although maintenance teams have strong technical expertise, they often don’t have the budgetary authority or organizational access for expansion, which can add delays to any larger initiative. The recommendations and approval from teams on the shop floor will generally still need buy-in from senior management. For successful scaling, it’s important to have these senior managers in the conversation from the beginning.
Whether your approach to digital transformation is to leverage an internal innovation group, focus on overall supply chain improvements, or leave the analysis to the experts on the shop floor, machine health monitoring solutions for the IIoT need to have a meaningful place in your digital transformation strategy.
To learn more about how machine health is at the heart of digital transformation — drop us a note.
Lauren is an Enterprise Account Manager specializing in relationship and business management with Augury’s commercial and industrial clients, supporting their organizational change management and helping to unlock value for corporate stakeholders. She has 10 years of experience in account management, customer success, and supporting organizations in their digital transformation journey. Lauren holds a BA from Mount Holyoke College and an MA from George Washington University’s Elliott International School in International Trade and Investment.