The Total Economic ImpactTM Of Microsoft HoloLens 2 With Mixed Reality Applications

Training Productivity Improvement And Materials Cost Savings

Evidence and data. Prior to the deployment of Microsoft’s HoloLens 2 mixed reality (MR) solution, interviewees’ organizations trained technicians — especially skilled manufacturing technicians — with traditional approaches, such as in-class PowerPoint presentations, training videos, and on-hands instruction on expensive and limited machines. Most interviewees cited how Microsoft’s MR solution enabled self-guided mixed reality instructions, leveraging 3D models, simulations, and real-world overlays to enable factory technicians to learn faster, understand content better, and practice machine-specific skills. Technicians could also observe and participate in remote demonstrations and be evaluated for certification, saving time and expense. Some interviewees described how creating digital twins of these sophisticated machines enabled them to reduce virtual, hands-on training without disrupting production time. It should be noted that training of field technicians (an important cohort, but not critical to manufacturing operations) is not included here.

As the expenses associated with developing training materials for MR technology are included in the Cost section, the corresponding cost savings of not having to produce traditional training materials is the second component of this benefit.

This specific training benefit speaks to the amount of training effort or cost that was reduced when the interviewees’ organizations deployed Microsoft’s MR solution. The key metric described by most interviewees was the reduced overall training time for skilled manufacturing technicians, also referred to as the door-to-floor reduction in time compared to their prior states. Interviewees shared many examples of training productivity improvement and materials cost savings benefits, along with data insights, including the following:

• The senior training program manager at a semiconductor supplier stated: “Existing engineers probably go to one training class a year, and new hires are probably going to go to two more. It depends. Because of the way our service model is, our customers know they have a certified engineer working on the tools. If we hire somebody whilst he can go and he can shadow in the field, he can’t truly do his job until he’s certified on at least one tool.”
• The senior manager, engineering services support and process systems development at a transportation manufacturing firm provided their perspective: “So, a training could take 20 days — it’s been reduced to 15 days. And also, to get the person to a professional or to a certified trainer, usually that process takes up to 40 to 45 days … and now we’re seeing that reduced by another seven days.”
• The engineering project lead for a semiconductor manufacturer spoke about their goals for the MR technology for training, noting, “Our goal was from our baseline that we really wanted to achieve a 50% improvement in training and a 50% reduction in trainer burden.”
• Interviewees noted that the reduction in overall training time for manufacturing technicians ranged from 19.4% to 30%. The weighted average of this same metric from the survey yielded 19.9%. Blending these data points results in an average of 23.5%.
• Interviewees provided ranges for time required to train new technicians both before and after the deployment of MR technology. Predictably this varied by organization and was largely based on the sophistication of their equipment. It ranged from 62 days before to 50 days after; six months down to four months; and aspired to cut six to nine months of training by 50%.

Modeling and assumptions. The focus of this benefit is training productivity improvement enabled with Microsoft’s MR solution with the key metric being the reduction in training time for skilled manufacturing technicians — both new hires, and existing technicians being trained on new equipment. Also included is the saving in materials costs compared to the prior state of training. Forrester modeled the impact for the composite organization assuming the following:

• The composite organization needs 150 new skilled manufacturing technicians per year for factory expansion. However, with an assumed 5.0% attrition rate, this implies that 445 new technicians need to be hired and trained in Year 1. Correspondingly, 5,850 of the existing manufacturing technicians need incremental training in Year 1.

• Forrester conservatively models that the full impact of deploying the Microsoft’s MR solution is 20% in Year 1, 22% in Year 2, and 24% in Year 3. It is worth noting and clarifying the difference between this holistic metric compared to a similar metric identified in a previous Microsoft MR study, titled, “The Total Economic Impact™ Of Mixed Reality Using Microsoft HoloLens 2.” For the current study, we focus on the total door-to-floor training time reduction, including the time expended to learn HoloLens 2 and the applications. In the prior study, there was a 75% reduction in training time for specific training components that were replaced by HoloLens 2.⁴ Even with a 20% to 24% reduction in door-to-floor training time for the current study, the total number of training hours saved are significantly higher than the prior study.
• Given the Industry 4.0 focus for the composite that is manufacturing leading edge products with complex machinery, Forrester models eight weeks of training at 25 hours per week for new technicians, which is 200 hours for the first year before the use of MR technology. For existing technicians, a more modest 10 hours of training per year is assumed.
• The fully burdened annual salary for the average manufacturing technician is $54,000, even for a global enterprise with varying pay scales due to the sophistication of these technicians. This computes to an average hourly rate of $26.
• For the training of manufacturing technicians, it is assumed that enough HoloLens 2 devices are available to adequately train the new technicians for the required hours, as well as the existing technicians for their relatively lower number of training hours. Thus, the deployment ramp for the Microsoft MR technology is assumed in row A9, which reflects the training ramp.
• The cost of training materials is a weighted average of $1,000 per new trainee and $250 per existing trainee.
• Deploying MR technology saves the composite organization 35% on traditional training materials expenses.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• Mixed reality’s ability to supplement or replace training and its associated benefit will depend on the specific users, tasks, and functions.
• Training savings hinge on the upfront investment of building relevant and high-quality MR curricula.
• Savings recaptured will depend upon the number of users reached and their average labor cost.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.91 million.

Improved Revenues From Training Effectiveness

Evidence and data. As noted in the previous benefit, prior to the deployment of Microsoft’s HoloLens 2 MR solution, interviewees’ organizations trained skilled manufacturing technicians with traditional approaches. With Microsoft’s MR solution, several interviewees described how creating digital twins of these sophisticated machines enabled them to achieve faster door-to-floor time specifically for new technicians basically, cutting down overall training time compared to how training was conducted previously. Doing so resulted in not only improved training productivity that we already discussed, but also improved time to revenue for existing factories bringing on a steady stream of new hires.

In addition to the faster ramp for new trainees, interviewees emphasized the improvement in the quality of training with Microsoft’s MR solution. Hands-on training with a digital twin would be akin to flight simulator training for a pilot. Some interviewees described this improvement in quality in terms of reduced scrap materials, anecdotal observations, and aspirational goals. This improved quality benefit applied to all skilled technicians delivering higher-quality products (improved yield) by being trained on the Microsoft MR solution.

This benefit discusses the amount of training effort or cost that was reduced when the interviewees’ organizations deployed Microsoft’s MR solution. The key metric described by most interviewees was the reduced overall training time for these skilled manufacturing technicians or the door-to-floor reduction in time compared to the prior state. As the expenses associated with developing training materials for MR technology are included in the cost section, the corresponding cost savings of not having to produce traditional training materials is the second component of this benefit. Interviewees shared examples of door-to-floor productivity improvement, along with data insights, including the following:

• The director of augmentation engineering services at a pharmaceutical manufacturer explained: “So then you take them to the floor and now they see the exact same instructions and they have the exact same media referencing the instruction just as they had in training. The difference is with using the HoloLens 2 is that you don’t have to have the digital twin now because you have the real machine.”
• The engineering project lead for a semiconductor manufacturer further expanded on their goals for Microsoft’s MR technology, stating, “Our goal is a reduction in training time — reduction in trainer burden and a 50% improvement in training quality.”
• The lead solution engineer of intelligent automation and AIOps infrastructure services provided their perspective, noting “I think at we see probably a 5% reduction in scrap which I think that’s pretty significant.”
• Interviewees spoke about the potential benefits of higher production quality driven by improved training, but there was only a single quantitative data point of a 5% reduction in scrap materials.

Modeling and assumptions. The focus of this benefit is faster time to revenue enabled with Microsoft’s MR solution, with the key metric being the reduction in door-to-floor training time for newly hired skilled manufacturing technicians. The second component of this benefit is the improvement in revenues due to the production of higher-quality products as a function of higher-quality training with MR technology. Forrester modeled the impact for the composite organization assuming the following:

• The composite organization has 295 new technicians that require training in Year 1.

• Forrester models eight weeks of training at 25 hours per week for new technicians, which is 200 hours for the first year before the use of MR technology.
• Based on the analysis of various data points for benefit A, Forrester conservatively models that the full impact of deploying the Microsoft’s MR solution results in a door-to-floor training time reduction of 20% in Year 1, 22% in Year 2, and 24%.
• The revenue generated per skilled technician, based on the composite characteristics, is $1,442 per hour in Year 1 (improving with productivity and learnings). It is worth noting that the revenue generated per average factory employee is $144 per hour. The reality is that the composite organization would not be able to meet its revenue targets without the key role played by the skilled manufacturing technicians. To be conservative, Forrester applies a 50% productivity adjustment.

• For training manufacturing technicians, it is assumed that a sufficient number of HoloLens 2 devices is available to adequately train the new technicians for the required hours. Thus, the deployment ramp for the Microsoft MR technology is assumed in row B7, which reflects the training ramp.
• For the second component of this benefit — improved quality of production — it is assumed that the benefits of higher-quality training enabled with Microsoft’s MR solutions accrues to all skilled technicians.
• To be conservative, Forrester assumes a 2.5% improvement in production quality enabled from the Microsoft MR solution.
• The annual revenue per factory employee for the composite is computed to be $240,000 in Year 1.

• To determine the net business impact for the composite, the revenue benefit is converted into operating profits. The model assumes an operating margin of 15% for a higher-end complex manufacturer.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• Variations in percentage improvement in production quality across different manufacturing organizations.
• Differences in annual revenue per factory employees by organization and region.
• Variations in operating margins across different types of manufacturing businesses.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $4.5 million.

Manufacturing Operations Productivity Improvement

Evidence and data. Prior to the deployment of Microsoft’s HoloLens 2 MR solution, manufacturing technicians typically had to refer to instruction manuals and reference charts during their day-to-day tasks of operating machines during production time. Most interviewees discussed the productivity benefits enjoyed by these technicians when having access to HoloLens 2 lenses and Guides software to see and manipulate advanced instructions, schematics, and HoloLens vital information that is overlaid on the real world, while remaining head-up and hands-free. Again, the value of Microsoft’s MR solution was most impactful for the skilled technicians working with advanced and sophisticated manufacturing equipment, who were higher-compensated workers compared to regular factory workers.

Interviewees noted that technicians also used remote collaboration applications, such as Remote Assist, to quickly get support from peers or experts, especially for troubleshooting. While there was an aspect of easier access to subject matter experts (SMEs) on sophisticated manufacturing equipment for these skilled technicians, the bulk of that benefit accrued to the manufacturing SMEs and is modeled in benefit F.

This benefit addresses the manufacturing productivity improvement for skilled technicians deploying Microsoft’s MR solution. The key metric extracted from the survey was the increase in task efficiency for these skilled manufacturing technicians, as it applies to tasks that could be enhanced with MR technology.

The director of augmented engineering services working in pharmaceuticals manufacturing said: “If you think about it, you’re investing in the operator. You give them the information they need when they need it. You’re giving them the ability to call for help even if they still have questions about whatever that task is. It’s been extremely beneficial.”

Modeling and assumptions. The focus of this benefit is manufacturing productivity improvement enabled with Microsoft’s MR solution with the key metric being increased task efficiency for skilled manufacturing technicians for ongoing operations enabled with MR technology. This benefit does not attempt to capture any productivity benefit for faster resolution of downtime or troubleshooting incidents, as that value is calculated in benefit D. Forrester modeled the impact for the composite organization assuming the following:

• The composite organization starts with 6,000 skilled technicians in Year 1 and adds a net of 150 new technicians each year based on the rollout of additional manufacturing lines.

• For manufacturing operations, it is assumed that the composite does not have sufficient HoloLens 2 devices available to adequately equip the number of technicians even when shared by five technicians, as assumed. Thus, the deployment ramp for the Microsoft MR technology assumed in row C2 is the much more modest operations ramp.

• The percentage of tasks that are enabled by MR technology for skilled technicians varies by the type of equipment and the products manufactured. The composite experiences a range of 15% to 17% from Year 1 to Year 3.
• The primary metric for this benefit, task efficiency improvement with MR for manufacturing technicians, is 20%.
• Consistent with benefit A, the fully burdened annual salary for the average manufacturing technician is $54,000, which computes to an average hourly rate of $26.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• Differences in numbers of skilled technicians across organizations.
• Variations in adoption of MR technology across organizations.
• Varying levels of efficiency gains in tasks by manufacturing technicians across different organizations.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.21 million.

Revenue Assurance From Avoided Production Downtime

Evidence and data. Irrespective of products produced or manufacturing technology, interviewees noted that the process of manufacturing complex products with sophisticated equipment was fraught with risks of downtime. Planned downtime generally refers to time scheduled for equipment maintenance and process upgrades, etc. Unplanned downtime could be especially pernicious and potentially crippling for the interviewees’ organizations. Sophisticated machinery could fail, break down, or sometimes need to be recalibrated during operational runtime. This was above and beyond any power failure or network performance degradation. Before the adoption of Microsoft’s HoloLens 2 MR solution, when interviewees’ organizations experienced equipment-related downtime, the manufacturing SME on the machine (an in-house expert) needed to be called and — more than 50% of the time — had to come in to evaluate the situation. The SME would then have to get on the phone with an expert from the vendor, who produced the specific equipment and diagnose the problem. In the most extreme of cases, the vendor’s expert might have to travel in or the equipment would have to be swapped out. Needless to say, countless hours could be spent merely diagnosing the root cause of the problem.

With the introduction of Microsoft’s MR solution, expert technicians were able to use remote collaboration applications, such as Remote Assist, to quickly get support from manufacturing SMEs for equipment troubleshooting. Faster troubleshooting for nonmaintenance machine downtime enabled faster time to revenue for existing factories. Clearly, MR technology could not avoid or fix the problem, but it enabled the interviewees’ organizations to communicate efficiently and cost-effectively to get the issue resolved.

This benefit speaks to the faster troubleshooting for nonmaintenance machine downtime resulting in faster back to production time when the interviewees’ organizations deployed Microsoft’s MR solution. The key metric described by most interviewees was the reduced downtime for factory equipment compared to the prior state. Interviewees shared examples of faster back to production from equipment troubleshooting, including the following:

• The director of augmented engineering services at a pharmaceutical manufacturer explained: “I would easily say [equipment breaks] three to four times per eight-hour shift per line that’s running. These lines are so finicky, and when you’re dealing with the variables of components and if a component changes by one millimeter, it could impact the flow of the line.”
• The engineering project lead for a semiconductor manufacturer spoke about their goals for the MR technology for training as: “I would say [for] one vendor or manufacturer [there is a critical breakdown] once or twice a year because the technology we have been running is an older one … that would be much higher when you’re running a new technology and you’ve got new equipment that you’re still learning.”
• The senior manager, engineering services support and process systems development at a transportation manufacturing firm provided their perspective, noting “It’s not just because you can’t travel but it’s because a plant is a 14- to 16-hour flight away makes travel very hard.”
• The lead solution engineer of intelligent automation and AIOps infrastructure services provided their perspective, stating, “We have anywhere from three to five of those trips that are being avoided every month.”
• Interviewees provided estimates for the frequency of downtime incidents in a factory production line, largely varying by the size of the organization and the complexity of the manufacturing process.

Modeling and assumptions. This benefit focuses on the faster back-to-production timeframe for troubleshooting of manufacturing operations enabled with Microsoft’s MR solution. The key metric is the reduction in factory downtime caused by equipment malfunction or failure. Forrester modeled the impact for the composite organization assuming the following:

• Forrester conservatively assumes the composite organization experiences five downtime incidents per factory per month. This translates into about 90 downtime incidents for the composite in Year 1 for any single factory.

• The average downtime per incident is pegged at 8 hours before the use of MR technology, which seems conservative for a complex manufacturing process with sophisticated machinery. The reduction in factory downtime due to Microsoft’s MR solution is 23.5%.
• For manufacturing operations, it is assumed that the composite does not have sufficient HoloLens 2 devices available to adequately equip the number of technicians even when shared. Thus, the deployment ramp for the Microsoft MR technology assumed in row D5 is the much more modest operations ramp.

• The single factory revenue per hour for the composite is computed to be over $144,000 in Year 1.

• It is further assumed that any such singular machine failure or malfunction impacts one given production line per incident but is multiplied across the number of overall factories in full production mode.
• To determine the net business impact for the composite, the revenue benefit is converted into operating profits. The model assumes an operating margin of 15%.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• Variations in frequency of downtime incidents in factory production lines across organizations of different sizes and manufacturing complexity.
• Variations in the deployment of HoloLens devices across organizations.
• Differences in single factory revenue per hour across organizations.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.04 million.

Field Technician Productivity Improvement

Evidence and data. Interviewees noted that prior to the deployment of Microsoft’s HoloLens 2 MR solution, field technicians typically had to refer to instruction manuals and reference charts during the course of their day-to-day tasks of installing and servicing manufactured products in the field. Interviewees discussed the productivity benefits enjoyed by these field technicians when having access to Microsoft’s MR solution using head-up, hands-free instructions enhanced by detailed visualizations overlaid on the real world. Real-time remote collaboration enabled “see what I see” assistance from and with manufacturing SMEs to complete work or resolve issues beyond the workers’ expertise without requiring extra trips. Field workers consequently saved time, prevented errors and rework, avoided excess trips, and increased their capacity.

This benefit addresses the productivity improvement for field technicians deploying Microsoft’s MR solution. The key metric extracted from the survey was the increase in task efficiency for these field technicians, as it applies to the tasks that can be enhanced with MR technology.

The department manager of field services in automotive manufacturing said that “Ultimately, it comes down to time to resolution of the customer. If he can cut it from four or six days down to one day or two days, it’s a benefit for all, but ultimately, it’s a benefit of customer experience.”

Modeling and assumptions. The focus of this benefit is productivity improvement for field workers servicing or upgrading manufactured products with the key metric being increased task efficiency for field technicians enabled by MR technology. Forrester modeled the impact for the composite organization assuming the following:

• The composite organization starts with 1,000 field technicians in Year 1 and adds a net of 40 new technicians each year based on organization growth.

• For field operations, it is assumed that the composite does not have sufficient HoloLens 2 devices available to adequately equip the entire fleet of field technicians. Thus, the deployment ramp for the Microsoft MR technology assumed in row E2 is the much more modest operations ramp. However, the number of field technicians with access to HoloLens 2 lenses is multiplied by a factor of 1.2 (line E3) because it is easier to share a lens in a field setting across 10+ users, compared to a manufacturing line.

• The percentage of tasks that are enabled by MR technology for field technicians varies by the type of equipment and the products manufactured. The composite experiences a range of 30% to 32% from Year 1 to Year 3 is assumed — basically one-third of field technician tasks are enhanced with MR technology.
• The primary metric for this benefit, task efficiency improvement with MR for field technicians, is 25%.
• The average field technician is available for 30 hours of productive work (not traveling or in transit) for 50 weeks per year.
• The fully burdened annual salary for the average field technician is $70,000, which computes to an average hourly rate of $45. The higher rate, compared to the average manufacturing technician, is based on the assumption that field service locations will mostly be in major city hubs.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• MR’s ability to aid task work will vary by specific supported tasks and depend on the availability of remote experts and site conditions, such as heat, sunlight, safety risks, and network connectivity.
• Achieving savings relies on building relevant and high-quality MR guides and/or models, for which the availability and cost of getting the right data to feed 3D models can be a significant inhibitor.
• Recaptured savings will depend upon the number of users reached and their average labor cost.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $1.76 million.

Manufacturing SME Productivity Improvement

Evidence and data. Interviewees reported having specialized experts, or SMEs, that were employees with machine/tool-specific expertise, providing business-critical work and playing key roles in: 1) assisting with manufacturing operations problem-solving and 2) assisting field technicians with product servicing and upgrading. Prior to the deployment of Microsoft’s HoloLens 2 MR solution, interviewees noted their skilled manufacturing and field technicians typically had to refer to instruction manuals and reference charts throughout the course of their day-to-day tasks as noted in benefits C and E. With the introduction of Microsoft’s MR solution, expert manufacturing technicians and field technicians used remote collaboration applications, such as Remote Assist, to quickly get support from manufacturing SMEs for equipment troubleshooting and dealing with product issues in the field. These experts used MR remote support for critical needs to avoid travel, boost capacity, and address needs more efficiently. Interviewees cited a varying range of travel time required for these SMEs in responding to factory downtime incidents — sometimes even days.

This benefit addresses the productivity improvement for SMEs deploying Microsoft’s MR solution to assist both skilled manufacturing and field technicians. The key metric extracted from the survey was the increase in task efficiency for these SMEs, as it applies to the tasks that could be enhanced with MR technology.

The lead solutions engineer of intelligent automation and AIOps infrastructure services in the power management manufacturing industry said: “A lot of time was getting consumed [with the] subject matter expert telling them [what to do]. We wanted to have this onboarding [happen quickly]. We started with digital training. We had the animation of each and every step — how to fix the screw and all the fun stuff.”

Modeling and assumptions. There are two primary components of this benefit as it relates to the productivity of SMEs. The first is the time saved in training expert manufacturing technicians, which is the other side of benefit A that accrues to these experts. The second is the collective time saved by avoiding travel to factories (to assist expert technicians with manufacturing equipment issues) and to field locations (to assist field technicians with product-related issues). In addition to the key metric of increased task efficiency for these SMEs, the reduction in training time metric from benefit A also comes into play. Forrester modeled the impact for the composite organization assuming the following:

• The composite organization employs 48 manufacturing and product SMEs globally.

• The training deployment ramp for Microsoft MR technology is assumed to be 63% in Year 1, 81% in Year 2, and 100% in Year 3.

• Each SME spends an average of 400 hours per year on training, whether it is for manufacturing or field technicians.
• The reduction in overall training time with Microsoft’s MR solution is 20% in Year 1, 22% in Year 2, and 24% in Year 3, consistent with row A6 in benefit A.
• The number of critical manufacturing incidents that would previously require travel for these SMEs is consistent with row D1 from benefit D.
• Forrester assumes an average of 18 hours of trave time per critical incident.
• The percentage of such critical incidents that can be resolved remotely by using MR technology is assumed to be 50%. This assumption balances the average travel time estimate.
• The key metric for increased task efficiency for SMEs with the deployment of MR technology is 30%.
• The fully burdened annual salary for the average SME is $166,000 due to the sophistication of these experts. This computes to an average hourly rate of $80.

Risks. The expected financial impact is subject to risks and variation based on several factors:

• The role of experts, the tasks they support, and the frequency and distance of their travel.
• The scope, quality, and adoption of instructions and remote assistance to task workers with MR.
• The number of experts affected and their average annual salary and travel costs.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.2 million.

Improved Time To Revenue For New Factories Ramping Online

Evidence and data. For the interviewees, building and equipping an Industry 4.0 factory for complex products was a multiyear journey. The construction of the building and infrastructure (e.g., electrical wiring, cabling, water and cooling, etc.) was beyond the scope of this study. Planning the production lines with the sophisticated machinery that has been discussed — the equipping component — came up for discussion during several interviews. In the prior state, such planning required working closely with equipment vendors, estimating size and form-factors, creating 3D models, etc. But the ultimate test came when the equipment arrived at the factory and was physically installed. Interviewees spoke of variances in specifications and human errors in estimating functional flow that led to equipment not fitting, requiring rework (with each engineering change order being upwards of $10,000). Inevitably, this led to delays in getting new factory lines and new factories ramping up production.

With the introduction of Microsoft’s MR solution, creating digital twins of equipment during the factory/line-planning process with HoloLens 2 and RA ensured that machines would fit and would not require engineering change (and thus more cost). With up-front planning, interviewees cited a significant reduction in the effort required to install equipment when building out a new factory line. Plus, the more significant impact on the business was that up-front planning allowed for faster time to revenue for new production lines.

There are two components of this benefit: the reduction in effort required to install machinery for each incremental production line and faster time to revenue for each incremental line. The key metric computed in the model, based on data provided by the interviewees, was more than an 80% productivity boost for manufacturing technicians installing equipment for a new production line (savings in FTEs and number of hours). The faster time to revenues for a new production line was also based on data provided by interviewees. Interviewees shared examples of door-to-floor productivity improvement, along with data insights, including the following:

• The lead solutions engineer of intelligent automation and AIOps infrastructure services provided their perspective: “Typically in the past, the plant would wait for all of that equipment to arrive on-site and have to use the physical equipment to be able to perform those analyses, and it usually took four to five employees. And so, we have total labor hours of around 60 hours for each piece of equipment that would arrive. With the way that we are able to utilize the HoloLens and can still work on that equipment, the plant was able to cut that down to essentially two people in about 10 labor hours for each of the equipment.”
• The engineering project lead for a semiconductor manufacturer spoke about how their organization used Guides as part of the process of building new factories: “Where we’ve used it and what we use [Guides] for is that as we’re building our factories … Our first team, the construction team, would use a HoloLens to overlay digital models for QA/QC control and to minimize rework, our clash on what we would call base build.” The engineering project lead for a semiconductor manufacturer also said: “What [Guides] can do is very much prevent delays because often these things need to happen in a sequence. And if something falls behind because something needs an expensive rework or something wasn’t caught, then it could have a knock-on effect of 10 other things and it could delay a whole thing that would then usually be pulled back in.”
• The senior training program manager at a semiconductor supplier stated: “Let’s say I’m building a new fab. I’m going to equip it with mixed equipment but there’s a whole bunch of our stuff in there and if I can sort of visualize the space and you give me the equipment parameters. I’m now building a space on this fab line or whatever and I’m able to prepare my facility for the equipment that’s coming in. In fact, I may even give you feedback and say, ‘Can you cut this down by an inch or centimeter something like that?’ And, therefore, my time to ramp up a new fab is reduced by two or three weeks. That’s time to money.”
• In terms of the second component of this benefit, which is faster time to revenues, only one interviewee was willing to estimate the likely reduction in time to ramp a new production line with the use of MR technology, which was two weeks (cited as a conservative estimate).

Modeling and assumptions. The focus of this benefit is faster time to revenue enabled with Microsoft’s MR solution for ramping up new production lines with the key metric being improved productivity for factory technicians equipping each new production line. The second component of this benefit is the revenues derived by ramping each new production line faster than before as a function of planning each line with digital twins by deploying MR technology. Forrester modeled the impact for the composite organization assuming the following:

• The composite brings on five new production lines each year and each production line has 10 unique equipment components.

• In the prior state, it is assumed that five factory workers are needed for 60 hours for each new piece of equipment installed.
• By using MR technology to build digital twins of each piece of equipment and a 3D rendering of the factory layout, the composite deploys each new piece of equipment using two factory workers for 20 hours each. This computes into a productivity improvement of 86.7% for equipping, installing, and calibrating each new production line.
• For manufacturing SMEs and other experts involved in the virtualization of the planning new production lines, it is assumed that a sufficient number of HoloLens 2 devices are available for these efforts. Thus, there is no deployment ramp adjustment for the first component of this benefit.
• Given the reduction in hours to install and calibrate all the equipment for a new production line (400 hours per line), Forrester estimates that the composite organization likely accelerates the time to ramp a new production line by two weeks, or 192 hours for the composite, which runs three 32-hour shifts per week.

• The annual revenue per production line per hour for the composite is $14,423 in Year 1.

• Line G11 applies the “training” deployment ramp, vs. the operations production ramp for Microsoft’s MR technology. Again, this is because this acceleration in time is not deterred by the availability of sufficient devices on the production line, but rather used by a small group of manufacturing SMEs and other production planning experts.

Based on the information provided, the deployment ramp for the Microsoft MR technology at is as described in row G11.

• To determine the net business impact for the composite for the second component of this benefit, the revenue benefit is converted into operating profits (which is assumed at 15%). That amount is added to the first component of this benefit — the productivity savings for installing equipment for new lines.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• Variations in the number of new production lines brought on per year across organizations.
• Differences across organizations in the number of factory workers needed for each new piece of equipment.
• Variations in annual revenue per production line per hour across organizations.

Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.68 million.

Overall Travel and Incidentals Savings

Evidence and data. Replacing expert travel with remote expertise and self-guided task worker instruction saved the interviewees’ organizations significant travel and incidentals costs (e.g., flights, cars, hotels, food and beverage, etc.) in addition to labor saved (which is captured separately, under productivity benefits). Interviewees noted costs saved were typically between $2,500 to $3,500 per trip. Avoided regional field worker trips for rework and follow-up visits also generated minor cost savings for fuel and incidentals. Training travel cost savings for new technicians were also experienced. Field technicians and manufacturing SMEs reduced overall travel due to MR technology.

Interviewees shared many examples of overall travel and incidentals savings benefits, including the following:

• Most interviewees reduced or eliminated one to two weeks of travel for new technicians who usually received some baseline training at hubs.
• Field technicians reduced their travel time by 20% to 35% by not having to travel, even locally, to assist customers with product issues that could now be handled by MR technology.
• Manufacturing SMEs previously had to be called into a factory that was experiencing equipment-related downtime. With Microsoft’s MR technology, the interviewees’ organizations avoided between three to 12 visits per factory location per week for these SMEs.

Modeling and assumptions. Forrester modeled the impact for the composite organization assuming the following:

• From a training standpoint, new technicians typically took a one-week trip in the prior state, while manufacturing SMEs (their trainers) used to take two one-week trips previously. The composite organization reduces 45% of training-related travel.
• The expense of a one-week trip — for both new technicians and SMEs — is estimated to be $2,500 for planned training purposes.
• Field technicians typically spent 25% of their time on travel before the use of MR technology. Field technicians eliminate 20% of this travel time due to MR technology.
• The cost per skilled technician per hour for local travel is based on their hourly expense plus $10 per hour on incidentals.
• For manufacturing SMEs who previously had to be called into each critical incident at any given factory, a 50% reduction in such travel is achieved with MR technology consistent with benefit F.
• The expense of a critical incident trip for an SME is conservatively estimated at $2,500, which is likely understated for trips that are arranged at the last minute.

Risks. The expected financial impact is subject to risks and variation based on several factors, including the following:

• The scope, quality, and adoption ramp of MR technology.
• The number of new technicians and SME trainers involved in training each year.
• The number of SMEs and field workers affected and their frequency of trips.
• The typical distance, length, tier, and amount of advance notice of avoided trips for SMEs.
• The typical travel cost and incidentals incurred per field technician trip.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.09 million.

Qualitative Benefits

Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify include:

• Furthered sustainability goals. MR instructions with HoloLens 2 allowed the interviewees’ employees to access training online and from anywhere, reducing the need for training-related travel. This saved time and money and helped meet sustainability goals more successfully since it reduced emissions associated with travel. This also reduced training material waste.
• Hands-free and remote training. Interviewees noted that holographic work instruction through Dynamics 365 Guides accessible via HoloLens 2 improved employees’ productivity with 3D, step-by-step, holographic step cards. This reduced errors, increased efficiency, ensured that procedure was followed safely, and overall improved the quality of work. Not only could training be accessed anywhere, but training could also be accessed in the work environment — not tied to a desk or mobile screen — to keep hands free to allow employees to receive training at their worksite. An IT technician could review a schematic on top of a device instead of watching a tutorial video. An employee working on a manufacturing line could see the next process step outlined over machinery while they were working at their station. The department manager in field tech services at an automotive manufacturing organization said: “Yes, you can use a mobile tablet or phone for technicians and experts to see the same thing, but they can’t work at the same time. And that’s why we chose here to use HoloLens. So, it gives the technician the flexibility to have both hands available to do what you must do.”
• Improved quality with enhanced employee experience. Providing an immersive training experience that allowed the interviewees’ employees the ability to train wherever, whenever in a head-up, hands-free environment. Along with more focused and efficient training sessions, interviewees’ organizations developed (and continually updated) process guides to conveniently help employees follow process steps or locate a best practice. This reduced errors and improved the quality of work.
• Attract, hire, and retain higher-quality employees. Interviewees noted their employees wanted to avoid spending time looking for information and wanted to get work done. With HoloLens 2, leveraging new technologies helped make work more interesting by providing new experiences and avoiding repetitive tasks. This improved employee experience, leading to improved retention and avoided hiring and transition costs — and avoided the loss of experienced employees and institutional memory. Leveraging HoloLens 2 and MRApps differentiated company recruitment strategies by using the latest and greatest technology, which also led to cost saving in acquiring and retaining high-talented employees.
• Protected health and safety. According to interviewees, MR instructions helped employees get through repetitive tasks more quickly — and could protect life and health. Not following procedures exactly as intended could lead to dangerous scenarios in a manufacturing context. HoloLens 2 with Guides enabled technicians to follow instructions that provided guidance and training while doing their work, ensuring procedures are followed safely.
• Improved compliance. Process guides helped technicians using HoloLens 2 follow the steps properly, helping meet compliance standards.

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement HoloLens 2 with MRApps and later realize additional uses and business opportunities, including:

• Expand the deployment of HoloLens 2 with MRApps to additional departments and roles. Businesses that adopt HoloLens 2 may find that there are more use cases for MRApps than were initially planned. With some additional investment for expansion, organizations can gain greater benefits by providing improved training quality and efficiency improvements to more employees.
• Redesign business processes and enhance decision-making by analyzing MR device and application data. With the ability to record trouble shooting scenarios and centrally collect and analyze such data, organizations may be better positioned to redesign and enhance existing processes.
• Adaptability for unexpected business challenges. HoloLens 2 allows business to rapidly adapt to unexpected challenges while avoiding disruptions to business continuity, The engineering project lead in the semiconductor manufacturing industry said, “We used it extensively and it paid for itself really just for one use case over COVID-19.”

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Appendix A).