IoT implementation practices: The value of experience We surveyed more than 600 business execs, IT professionals, engineers and other IoT stakeholders to learn about their companies IoT projects and share their experiences by project phase, company size and success level. By Sue Troy
3 AUTHOR S PAGE 4 EXECUTIVE SUMMARY 5 RESEARCH SYNOPSIS 6 INTRODUCTION 7 Project phase: At production scale 8 About half of firms underestimate IoT timelines 9 What it takes to drive an IoT project forward 10 Primary and secondary IoT benefits 12 For many, data and platform security is a top priority 13 In focus: University of Southern California 14 Project phase: Testing 16 Project phase: In research 18 Interest in IoT? 18 In focus: Dun & Bradstreet FIGURES 7 Figure 1: Practice makes perfect? 8 Figure 2: Project length estimates 9 Figure 3: Stakeholder sponsorship is key 10 Figure 4: Primary benefits 11 Figure 5: Factors impacting project success 12 Figure 6: Project challenges 14 Figure 7: How well are results aligning with expectations? 16 Figure 8: Project challenges (projects being tested) 17 Figure 9: Expected benefits (projects being researched) 19 APPENDIX 19 Figure 10: Production-scale projects: Results vs. expectations 20 Figure 11: Production-scale projects: Time to implement 21 Figure 12: Production-scale projects: Secondary benefits 22 Figure 13: In-testing projects: Primary benefits 23 Figure 14: In-testing projects: Secondary benefits 24 Figure 15: In-testing projects: Success factors 25 Figure 16: In-research projects: Stakeholder participation factors 26 Figure 17: No organizational action taken: Why? 27 Figure 18: Vertical industry 28 Figure 19: Company size: Employee count 29 Figure 20: Company size: Revenue 30 Figure 21: Business location 31 Figure 22: Job function 32 Figure 23: Job level TABLE OF CONTENTS 2
Sue Troy The IoT Institute Sue Troy is executive editor of The IoT Institute, where she writes and edits articles about the IoT ecosystem. She has spent more than 25 years writing and editing IT-focused content, with long stints at companies such as TechTarget and Ziff Davis Publishing. Her most recent role was as editorial director of TechTarget s CIO, IT Strategy and Channel Media Group, where she was most inspired by emerging technologies such as IoT, blockchain and artificial intelligence. AUTHOR S PAGE 3
EXECUTIVE Companies around the globe have high hopes for the Internet of Things and are eager to reap the profits projected by vendors and analysts. But, of course, it s not a simple process of installing some sensors, collecting the data and raking in (or saving) the money (or efficiencies or improved data). There s much research, planning and testing, and after that comes the heavy lifting of implementation. Though it s still early days of IoT, many companies have already gone down this road, whether at full production scale, testing IoT pilots or just researching IoT. We conducted research on those experiences, analyzing survey responses from more than 600 professionals either directly involved with or interested in IoT, comparing and contrasting results from the overall respondent base vs. those from large companies, those from small companies, those from manufacturing and those who reported excellent results from their production-scale IoT projects. The differences among these groups point to valuable insights about the state of IoT implementation. And those with excellent results from their production-scale projects may have the most important lessons to share. Some highlights from that group: Respondents who reported excellent results tended to have more projects under their belts. Respondents reporting excellent results were more likely to say that the results far exceeded their expectations. Those reporting excellent results were more likely to say that their project took much less time, less time or about as much time as planned than those without excellent results. Those with C-level sponsorship of IoT projects as well as involvement from all stakeholders were much more likely to report excellent results. Respondents who reported excellent results typically were less challenged by factors impacting their projects. Below we dive into these details and offer explanations for the survey findings SUMMARY 4
RESEARCH Survey name IoT Implementation Practices Survey Survey date July and August 2017 Region Global Number of respondents 618 Purpose To gauge the state of IoT projects and implementation practices within businesses Methodology The IoT Institute surveyed 618 professionals. To encourage prompt response and increase the response rate overall, the following marketing research techniques were used: A live link was included in the e-mail invitation to route respondents directly to the online survey. The invitations and survey were branded with The IoT Institute name and logo, in an effort to capitalize on subscriber affinity for this valued brand. A reminder email was sent to non-respondents. Each respondent was invited to participate in a drawing for one of four $100 gift cards. Survey respondents came from across a range of vertical industries, with manufacturing having the largest share, at 19.6% of respondents, followed by, in order, information technology; energy, power and utilities; education; government/public administration; construction; aviation/aerospace; warehousing, distribution and logistics; healthcare; agriculture; financial services; ground transportation; retail trade; and real estate, rental and leasing. Respondents to the survey were about evenly split between companies with fewer than 100 employees and those with more than 100 employees. About 18% of respondents came from companies with 5,000 or more employees. More than half of survey respondents (56.5%) came from companies with less than $100 million in revenue, and 9.4% came from organizations without revenue figures (government entities and other non-revenue-based organizations). About 75% of respondents hailed from North America (Europe and Asia/ Pacific followed next, at 10.4% and 7.6%, respectively), with the overwhelming majority of North American respondents coming from the United States. The largest group of respondents (26.7%) were from the business/organizational management job function. Following that was engineering, at 23.7%; IT, at 12.2%; product management/r&d, at 7.6%; and operations/facilities, at 6.9%. In terms of job level, the greatest share of survey respondents classified themselves as managerial level, at 24%, followed by director, individual contributor, owner, president/c-level, senior vice president or vice president, and supervisor. SYNOPSIS 5
The wave of initial hype surrounding the Internet of Things is arguably behind us now. Many intrepid IoT voyagers have already set sail for a new realm where physical objects, ranging from factories to fields, become digitized. Some businesses have already weathered their passage, avoiding marauders intent on plundering their riches on the open sea, and arrived on shore at their destinations, discovering new riches there. A sizable number of those who have begun the journey, however, have run into unforeseen obstacles or delays, while others, awaiting departure from the old world and preparing navigation charts for their own journeys, have much to learn from the explorers. To help you incorporate lessons from these pioneers, we are researching the state of IoT projects around the globe. The first research study in our new series examines IoT implementation practices at three phases: the early-planning stage, proof-ofconcept step and final deployment. Here we present detailed information about those projects, such as their benefits, project length, how well the results aligned with expectations and who the primary stakeholders were. We look at the overall respondent base, as well as how small-company respondents answers differ from those at large organizations. We also consider what sets apart manufacturing-sector respondents answers (manufacturing respondents represented the largest vertical industry in our survey, and we had enough data from that group to report on it as a segment). We hope you use this report to guide your own IoT projects and build out best practices to smooth the way for your future IoT endeavors. Of particular interest should be the findings from survey respondents who had excellent results in production-scale projects. These companies have learned valuable lessons, and your organization can benefit from their experience. In general, these firms are happier with the results of their IoT initiatives. They have a good sense of how long they will take, know who should be involved and an understanding of what it takes to succeed. INTRODUCTION 6
Project phase: At production scale The IoT Implementation Practices Survey, which surveyed 618 business and technology professionals about their companies IoT projects, indicates that enterprise and industrial IoT is on track to becoming mainstream. Roughly a quarter, or 160, of respondents companies had widely deployed an IoT project or projects at production scale. A total of 37.5% of those respondents reported between one and five IoT projects and 26% reported between six and 15 projects. Eleven percent of respondents with production-scale IoT initiatives reported having more than 100 projects. And, it seems, practice makes perfect, or better, anyway. Those respondents who reported excellent results tended to have more projects under their belts: 56% of this group had more than 15 production-scale projects, versus only 25% of those whose results were less than excellent. Respondents from large companies appeared more likely than smaller firms to have a production-scale IoT project, with 32.7% answering in the affirmative, compared with only 19.1% from those with fewer than 100 employees. The number of projects skewed higher for larger companies. Seventy-five percent of small companies with IoT projects had 15 or fewer projects at scale, compared with only 54% of those at organizations with more than a hundred employees. A total of 14% of large companies already have more than a hundred IoT projects under their belt. Only 5.2% of small companies said the same. enormous difference between projects like these and a major IoT effort like collecting, aggregating and analyzing terabytes or petabytes of data from aircraft engines or railroad cars. Among respondents with production-scale IoT projects, most seemed to be content with the results. Only 7.5% said that the results were fair, and less than a percent characterized the results as poor. The largest chunk (41%) rated the results as very good. Respondents with production-scale IoT projects mostly found that their initiatives met their expectations. Ninety-one percent of respondents said that their projects either far exceeded their 45% 40% 35% 30% 25% 20% Figure 1 Practice makes perfect? expectations (at 15.6% of those surveyed), somewhat exceeded expectations (25.6%) or met expectations (49.4%). Within the manufacturing sector, about 21% of the 119 respondents said that their project fell somewhat below expectations, higher than the overall respondent base. Respondents from large companies were more likely to say that the results of their projects far exceeded their expectations (18.4% vs. 8.6%). As you might expect, those reporting excellent results were more likely to say that the results far exceeded their expectations: 59% vs. just 5% of those without excellent results. How many distinct IoT-related projects has your company widely deployed at production scale? Respondents with excellent results All other respondents Analyst Kurt Marko described having such a percentage of large-company respondents reporting more than 100 projects as shocking and, he said, it points to a lack of consistency in the definition of an IoT project. I find it very hard to believe that even large companies have completed over 100 significant IoT projects. Thus, I suspect most respondents are including many small instrumentation projects, such as adding a new type of sensor or data collection to a manufacturing line or upgrading HVAC equipment with smart thermostats or controllers, he said. There s an 15% 10% 5% 0 1 5 6 15 16 50 51 100 More than 100 Don t know Base: 34 ("excellent") and 127 (all other respondents) 7
About half of firms underestimate IoT timelines About half of the organizations with production-scale IoT projects ran into delays. A total of 39% reported that it took longer than expected. Another 10% said it took much longer. Respondents from large companies were more likely than those with fewer than 100 employees to say that their project took longer than planned (44.9% vs. 28.1%). Those at smaller companies were more likely to say that the project took much longer than anticipated (19.3% vs. 6.1%). One possibility for the discrepancy is that larger companies can devote more resources to making sure that IoT projects stay on track. The manufacturing segment seems to have worse luck with delays than other sectors. About 55% of respondents from that sector reported that their project took longer (45.5%) or much longer (9.1%) than expected. Process complexity in conjunction with the challenges related to information technology (IT) and operational technology (OT) integration in manufacturing could explain that finding. Figure 2 Project length estimates How would you describe the time it took to implement this production-scale IoT project? Took much more time than planned Took much longer than planned Took longer than planned Respondents with excellent results All other respondents Manufacturing-segment respondents were on average more likely to work for larger companies than the typical survey respondent, and therefore liable to be involved with projects involving more stakeholders and more parts of the business. Those reporting excellent results were more likely to say that their project took much less time, less time or about as much time as planned than those without excellent results: 65% vs. 46%. What might explain that sizable difference? Marko said, The excellent group had more IoT expertise (about twice the percentage in the excellent group reported having 100 or more projects, compared with the non- excellent respondents) and better project governance processes. Thus, they knew what they were doing and getting into and did more upfront planning to create realistic schedules and allocate enough staff at the right times to complete the job. Took about as much time as planned Took less time than planned Took much less time than planned Base: 34 ("excellent") and 126 (all other respondents) 0% 5% 10% 15% 20% 25% 30% 40% 45% 50% 8
What it takes to drive an IoT project forward So how long did these projects take? The largest group (41.5%) said that it took six months to a year, and a quarter reported the project took between 12 and 18 months. About 17% reported their projects took less than six months. At small companies, almost two-thirds said it took less than a year, while that group was only about 55% at large enterprises. Within the manufacturing sector, only 45% said it took less than a year. And project length doesn t appear to have an impact on the success of the project: We didn t find significant differences on this metric among those who had excellent results. Perhaps most interesting is that those with C-level sponsorship of IoT projects are much more likely to report excellent results. In fact, all primary sponsor stakeholders we asked about showed a similar correlation. (The one exception to this were line-of-business leaders, which were described as primary sponsor in about equal percentages by both those who reported excellent results Figure 3 Stakeholder sponsorship is key and those who did not report excellent results.) The same held true when we considered those reporting excellent and very good results, compared with those who did not, but the difference between those two groups was less stark. These findings seem to indicate that the path to success in an IoT project calls for having more rather than fewer stakeholders involved as primary project Were each of the following involved in this production-scale IoT project as a primary sponsor? (Select all that apply.) As for stakeholders involved in the projects, C-level execs tended to be the primary sponsor (in 29% of cases but in 42.5% of cases in the manufacturing sector) and the budgetary approver (cited by 32% of respondents). Perhaps C-level execs at manufacturing companies take an expanded role in IoT initiatives because specialized technical companies tend to have leaders with engineering experience. Line-of-business specialists (cited by 30.5% of respondents) were more likely than other roles to be the technology approver of the project, while IT leaders were more likely to be the project architect/specifier (cited by 24% of respondents), and IT staff were more likely to be the project implementer (cited by 43% of respondents). At smaller companies, C-level execs were less frequently cited as a primary sponsor than at larger companies (21.7% vs. 33.3%). Also at smaller companies, conversely, C-level execs were more likely to be a technology approver than at larger companies (22.9% vs. 14.3%). This expanded role is likely a function of the fluid responsibilities common at small companies. 70% 60% 50% 40% 30% 20% 10% Respondents with excellent results All other respondents At smaller companies, CEOs tend to be more involved in day-today operations than at larger organizations. That fact is likely part of the reason why fewer C-level execs (4.8%) at large firms were involved in IoT projects than at smaller firms, where 10.3% were. 0 C-level execs Line-of-business Line-of-business Operations team IT leaders IT staff Consultants leaders Base: 33 ("excellent") and 127 (all other respondents) 9
Figure 4 Primary benefits What would you consider the primary benefit of this production-scale IoT project? Other Cost savings Improved production output quality Improved employee efficiency Improved production output quality Improved business awareness Improved customer data Improved customer experience Fewer than 100 employees 100 or more employees Manufacturing sponsors. This is an important lesson for businesses that are researching or planning IoT projects: When it comes to having a variety of stakeholders support IoT projects, less is not more. Marko was not surprised by the fact that projects with C-level and other stakeholder participation were more likely to succeed, but, he said, It s telling that having more stakeholders improves the chance of success. IoT projects touch many parts of the organization; data is often collected by one organization, processed and analyzed by another and used by yet different business groups. Having everyone involved in the project ensures that important details aren t left out, the data ends up being useful (and used) and when resources are needed, the relevant department will be more likely to pony up since they have already committed to the project. Primary and secondary IoT benefits The primary benefits of at-production-scale IoT projects were improved operational efficiency, cited by 37.5% of respondents, improved customer experience (20%), improved business awareness (10%), improved customer data (9.4%) and cost savings (6.9%). Small-company respondents were more likely than large-company respondents to cite cost savings as a primary benefit (15.5% vs. 2%). Small-company respondents were also less likely to cite improved customer data than respondents from large companies (5.2% vs. 12.2%). Improved operational efficiency 0% 5% 10% 15% 20% 25% 30% 35% Base: 58 (fewer than 100 employees), 98 (100 or more employees) and 33 (manufacturing) Marko was not surprised by the survey s finding that improved operational efficiency is a major benefit of IoT. IoT data is often used to find production or workflow problems, predict failures (replace reactive problem fixes with proactive maintenance) and tune machine parameters, he said. 10
Among secondary benefits, cost savings topped the list, cited by 29.4% of respondents. Improved operational efficiency was right behind at 26.9%, followed by improved customer data (24.4%) and improved production output quality (23.8%). Again, small-company respondents were more likely to name cost savings as a secondary benefit (37.9% vs. 24.5%). And, small-company respondents were more likely to list improved production output quantity as a secondary benefit, compared with large-company respondents (22.4% vs. 15.5%). Considering both primary and secondary benefits together, the top outcomes for IoT projects were in the following order: 1. Operational efficiency. 2. Customer experience. 3. Cost savings. 4. Customer data. 5. Production output quality. 6. Business awareness. 7. Employee efficiency. 8. Production output quantity. Figure 5 Factors impacting project success How important are/were each of the following to the success of this production-scale IoT project? Project business value Data relevance Data integrity Platform security Data security Platform ability to meet future needs Platform ability to meet present needs Project cost of ownership Functionality of edge devices Not at all important Not very important Somewhat important Very important Critical 0% 20% 40% 60% 80% 100% Base: 156 11
For many, data and platform security is the top priority For respondents with production-scale IoT projects, data security and platform security were more likely to be considered critical to the success of the project than the other factors, cited by 45.8% and 43.1% of respondents, respectively. Manufacturing-sector respondents also placed high value on platform business value, with 43.8% of respondents saying that it was a critical factor. Respondents tended to believe that the following factors were very important: Perhaps most interesting is that respondents with excellent results were more likely to say that all of these factors with the exception of data integrity were either critical or very important to the success of their project. It seems that taking these factors more seriously can lead to decisions that improve project outcomes. Figure 6 Project challenges How challenging are/were each of the following with regard to this production-scale IoT project? We then asked survey respondents how challenging the above factors were in their projects. Respondents were more likely to say that each of the factors were somewhat challenging than other options with one exception: The same percentage of respondents (32.9%) reported that data integrity was somewhat challenging and very challenging. Functionality of edge devices. Project cost of ownership. Platform s ability to meet present needs. Platform s ability to meet future needs Data integrity. Data relevance. Project business value. Within small companies, platform security appears to be the most critical concern, identified as such by 43.4% of those respondents. About an equal amount of large-company respondents cited platform security as a critical concern, but it wasn t the largest one: A full 50% of large-company respondents named data security as a critical concern (compared with 39.6% of small-company respondents). Not at all challenging Not very challenging Very challenging Somewhat challenging Project business value Data relevance Data integrity Platform security Data security Platform ability to meet future needs Platform ability to meet present needs Extremely challenging There could be multiple drivers that explain why large companies are more focused on data security. For one thing, they are more likely to be publicly held and face greater public scrutiny on their data security practices. In addition, larger companies tend to simply be more visible and valuable targets from the perspective of cybercriminals. Project cost of ownership Functionality of edge devices 0% 20% 40% 60% 80% 100% Base: 152 12
The manufacturing sector has unique IoT needs and must often deal with linking brownfield and greenfield technologies together while also driving unprecedented collaboration among different organizational divisions. This fact was likely the reason why respondents in this sector tended to be very challenged by the functionality of edge devices, which are often critical in such settings, and project business value. Consequently, manufacturing professionals reported not being as challenged by factors such as data security, platform security, data integrity and data relevance. Among all production-scale respondents, taking those who reported the above factors to be anywhere from somewhat to extremely challenging all together, respondents rated the challenges in the following order, from most challenging to least challenging: Functionality of edge devices. Cost of ownership. Project business value. Platform s ability to meet future needs. Platform security. Platform s ability to meet present needs. Data security. Data integrity and data relevance. Marko said that the functionality of edge devices tended to be more problematic for survey respondents because the heart of IoT is adding intelligence to edge devices, whether these are a manufacturing machine, HVAC controller, shipping container or delivery truck. The technology for adding intelligence is in many cases quite new, rapidly changing and not necessarily designed to interoperate with other IoT devices. Marko was surprised that data cleanliness (integrity and relevance) ranked last in terms of project challenges. He said, It s a significant challenge given the diversity of formats, frequent lack of metadata and complexity of designing big data analytics software where the old maxim garbage in, garbage out is more important than ever. The low ranking of data security also surprised him since, he said, many IoT devices are a security nightmare -- routinely hacked and used to spread malware. Security is often not designed into the device, making it difficult (or impossible) to either harden the device or encrypt the data as it s in transit. Among small-company respondents, project business value was more likely than at large companies to be considered extremely challenging (24.1% vs. 10.6%). In fact, project business value was the most frequently named as extremely challenging by small-company respondents. In general, large companies seemed to find extreme challenges more often, but not with regard to project business value. Marko said: "This is probably due to large organizations having a more sophisticated understanding of the capabilities and outcomes of an IoT project. Deriving business value doesn t happen automatically just by sprinkling some smart sensors or connected devices around your production floor or in your products. You need a plan on the data you want to collect, what it is measuring, the range of expected data and the implications and the decisions you can make based on the data. I expect that large companies thought these factors through in more detail before the IoT project. Respondents who reported excellent results typically were less challenged by these factors perhaps because they tend to be more experienced. In focus: University of Southern California The University of Southern California has more than a hundred productionscale IoT projects, launched among the various schools that make up the university system. The university s president, C.L. Max Nikias, has identified IoT as a major opportunity in the years ahead. Among the projects at the school are one at the Stochastic Semi-Autonomous Systems Lab, where research is aimed at such things as figuring out ways to reduce energy use in supermarket refrigeration systems and improve storage of energy. Another IoT project at the university is chartered with researching ways in which IoT can be a part of neighborhood-based augmented reality tours. Yet another project looks to employ wearable devices to help educators gather real-time data about how students are learning, which project sponsors hope will lead to better information around how to personalize instruction for each student. In addition, Gregory Sorensen, supervising computer engineer at USC, said that the university is installing smart network devices between buildings; edge networks will replace current technology. Facilities personnel get real-time alerts of air supply, temperature and humidity readings in all area of the campus, he said. This information enables us to collect and exchange data by the second, he said. The data is sent to an operations center, and if there is a problem, service personnel typically diagnose it in minutes rather than hours. Gregory Sorensen. Photo source: LinkedIn 13
Project phase: Testing Among survey respondents whose companies did not have production-scale IoT projects, about 18% (112 respondents) were testing IoT projects. A majority of those respondents (54.5%) expected the projects to be widely deployed within a year, and almost two-thirds were testing two or three IoT projects. In terms of how well expectations aligned with reality, about 15% said it was too soon to judge, and about 20% said that the project results either fell somewhat short of expectations or fell far short of expectations suggesting that those testing IoT projects had a bigger disconnect between expectations and reality than those with completed, production-scale projects. And within the manufacturing sector, the gap was larger: About 33% said survey results fell somewhat or far short of expectations. This gap in manufacturing is likely the result of the clash between the hype in this sector with all of its bluster of a coming industrial revolution versus the reality: It is difficult to get transformative gains from a piecemeal IoT solution and it is expensive to simply build a cutting-edge facility from scratch. In addition, there is often a culture clash between manufacturing professionals who are trained to focus on incremental improvements and the promise of technology vendors claiming to help transform their business. Marko suggested that the discrepancy between manufacturing respondents and large-company respondents (24% of whom said the projects fell somewhat or far short of expectations) relates to the complexity of the projects. Manufacturing projects likely entail more pieces of sophisticated production equipment from different manufacturers where both the difficulty of getting each individual IoT system to work properly is higher and the integration challenge of getting all the components to work together and interact (that is, readings from machine A cause changes in the operation of machine B) is great. Figure 7 How well are results aligning with expectations? Thus far, how have the results of this IoT project test aligned with your expectations? Don t know; too soon to tell Falling short of expectations Falling somewhat short of expectations Meeting expectations Somewhat exceeding expectations Far exceeding expectations Base: 52 (fewer than 100 employees), 58 (100 or more employees) and 33 (manufacturing) Fewer than 100 employees 100 or more employees Manufacturing 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 14
About 38% of respondents the most sizable group expect their IoT project to take from six months to a year to complete, about the same as among those with production-scale projects. In terms of stakeholder participation, the active testers had a roughly similar breakdown to production-scale project respondents, with one exception: Among active testers, line-of-business specialists were less likely to be involved as technology approver than among production-scale respondents (18.6% vs. 30.5%). In terms of primary benefit of the in-testing IoT project respondents, there were no big differences with the production-scale respondents: Both sets of respondents cited improved operational efficiency most frequently. The testers did look to have higher expectations around customer experience, with 29.5% citing that as a primary benefit, compared with only 20% of production-scale respondents, who reported with the benefit of actual results rather than expectations. Among respondents at companies with fewer than a hundred employees, the most frequently mentioned primary benefit was improved customer experience, at 34.6%, which compares with just 25.9% of large-company respondents. In terms of secondary benefits mentioned by the in-testing IoT project respondents, cost savings was the most cited response, like with the production-scale respondents. With regard to the factors that contribute to the success of IoT projects, those in testing had a similar profile to those respondents at production scale: Data security and platform security were more likely to be considered critical to the success of the project than the other factors, cited as critical by 44.5% and 40.9% of respondents, respectively. Small-company respondents were less likely to cite any of these factors as not at all important or not very important, suggesting that for small-company respondents, the IoT project stakes are high, and each project is more important to the company than at larger companies. At a small company, failure in a single project might kill the IoT initiative in its entirety. Diving a little deeper into that data, project cost of ownership and platform s ability to meet future needs were more important to small-company in-testing respondents than large-company respondents. Seventy-one percent and 76% of the former group said those factors were either very important or critical, compared with 53.5% and 62.5%, respectively, of big-company respondents. Data relevance, meanwhile, was more important to big-company respondents (86% said it was very important or critical) compared with small-company respondents (73.5%). The factors most often cited as very challenging to the testers were the platform s ability to meet future needs (32.7% of overall respondents and 50% of those from the manufacturing segment) and data security (31.8%). Most factors had higher percentages of in-testing respondents characterize them as somewhat challenging than very challenging. The platform s ability to meet future needs was mentioned as extremely challenging (cited by 15%) by in-testing respondents more frequently than any other factors. Small companies were more likely to be very or extremely challenged by functionality of edge devices (45% vs. 29%), while large-company respondents were more likely to be very or extremely challenged by the platform s ability to meet future needs (53.6% of large company respondents vs. 42% of small company respondents). 15
Project phase: In research Among survey respondents who had neither production-scale nor in-testing-phase IoT projects, about 11% (68 respondents) were actively researching IoT projects. The bulk of those respondents expected their projects to be widely deployed within three years, and almost two-thirds were researching two or three projects. The largest share (39.7%) of these respondents expected the project to take a year to 18 months to implement, from conception to production. In terms of stakeholder participation in the active research of IoT projects, the profiles were roughly similar to the other two groups: C-level execs were more likely than other roles to be the primary sponsor and budgetary approver of the projects, and IT staff were more likely than other roles to be the implementers. IT leaders were more likely to be the technology approver. Consultants (cited by 28.1% of respondents) also play an important role in IoT projects. Many companies call in outside experts early on in projects involving new technology, and as these individuals gain familiarity with the organization s needs, they frequently assume the role of architect/specifier. When it came to the expected primary and secondary benefits of the in-research IoT projects, there were several differences with the production-scale and in-testing respondents. In-research respondents were more likely to cite improved customer data as a primary benefit, reported by 20.6% compared with 9.4% and 8.9%, respectively. The researchers were also less likely to consider improved operational efficiency (cited by 15% of respondents), improved customer data (13%), improved customer experience (11%) and cost savings (11%) as secondary benefits. Figure 8 Project challenges (projects being tested) How challenging are each of the following with regard to this IoT project your company is actively testing? Project business value Data relevance Data integrity Platform security Data security Platform ability to meet future needs Platform ability to meet present needs Project cost of ownership Functionality of edge devices Base: 108 0% 20% 40% 60% 80% 100% Not at all challenging Not very challenging Somewhat challenging Very challenging Extremely challenging Uncertain/not sure yet 16
In looking at the factors that impact the success of an IoT project, the researchers answers mostly fell in line with those who have production-scale projects or are in the testing phase, with one exception: While data security and platform security were seen as critical to the success of an IoT project among all three groups, more than half of the researchers saw data integrity critical to the project s success, vs. only 33.6% of the testers and 36.6% of the production-scale respondents. Marko suggested that the researchers are benefitting from the experience of those who have fully implemented IoT projects. I suspect those already in the midst of an IoT implementation either didn t appreciate upfront the impact of data integrity on the project s success and/or are collecting a limited set of data targeted to a particular use case, whereby data integrity and consistency is less challenging, he said. Figure 9 Expected benefits (projects being researched) What do you anticipate would be the primary benefit of this IoT project your company is actively researching? Improved employee efficiency Improved business awareness Cost savings Other (please explain) 7% 3% 2% 3% 3% Uncertain/not sure yet 32% Improved operational efficiency 21% Improved customer data 29% Base: 68 Improved customer experience 17
Interest in IoT? Among those respondents not involved with an IoT project, either at scale, in testing or in research, about 60% said they were interested in implementing the technology. Customer demand and improved security were referenced as reasons more frequently than other factors, when respondents were asked which factors would motivate their companies to consider an IoT project, followed by lower cost to implement and proven success by competitors. In focus: Dun & Bradstreet Information services company Dun & Bradstreet has been researching IoT for about a year and expects to deploy two to three IoT projects within the next three years. Analytical consultant Kevin Conley is dedicated to the company s IoT efforts, one of about eight employees similarly focused on the technology. Dun & Bradstreet provides business information to enable credit lenders to decide who they will lend money to and how much they will lend. D&B plans to incorporate IoT-derived data from third-party sources to flesh out the information it provides customers, providing a more accurate picture of a company s creditworthiness. As an example, Conley pointed to a pizza shop that D&B has information on. D&B currently has some information about the pizza shop, said Conley, yet we don t have enough information to populate... the commercial credit score, the financial stress score, the D&B viability ratings score. We don t have enough information to tell us really how robust the company is. IoT changes that. By supplementing existing information with partner-supplied IoT data sources from, for instance, HVAC sensor monitors that measure heating and cooling at the pizza shop; electrical sensors deployed in the customer seating area that detect usage over time; and sensors within the pizza shop s waste bins that measure volume of activity, D&B can paint a better picture of the business vitality of the pizza shop, which is valuable for D&B s customers that may be considering making business decisions about the pizza shop. At D&B, the expected use of IoT represents a level of maturity beyond most companies using IoT: They are reliant on the successful implementation of IoT by other companies, to produce accurate IoT data that D&B can use in its business offerings. That s one of the challenges that we have to overcome. Many of the companies that we are trying to partner with are in the early stages of formulating their own IoT strategies. They re not ready yet to partner with a third party such as D&B, Conley said. He also said that some of the companies D&B is looking to partner with own or have access rights to the data but have privacy and security concerns that D&B has to work through, ensuring partners that the data will be protected and will only be used in aggregate. 18
Figure 10 Production-scale projects: Results vs. expectations How did the results of this IoT project align with your expectations? Met expectations Fell somewhat short of expectations 49% Base: 160 9% 16% Far exceeded expectations 26% Somewhat exceeded expectations APPENDIX 19
Figure 11 Production-scale projects: Time to implement From concept to production, how much time did this IoT project take to implement? 18 months to 24 months A year to 18 months More than 24 months 25% 11% 6% 17% 41% Less than six months Six months to a year APPENDIX Base: 159 20
Figure 12 Production-scale projects: Secondary benefits What would you consider the secondary benefit(s) of this IoT project? (Select all that apply.) Other (please explain) None of the above Improved production output quality Improved employee efficiency Improved production output quality Improved business awareness Improved customer data Improved customer experience Improved operational efficiency Cost savings Base: 160 0% 5% 10% 15% 20% 25% 30% APPENDIX 21
Figure 13 In-testing projects: Primary benefit What do you anticipate will be the primary benefit of this IoT project your company is actively testing? Improved employee efficiency Improved production output quality Improved business awareness Other (please explain) Improved customer data Improved customer data 6% 7% Cost savings 9% 5% 5% Base: 159 2% 3% 2% Uncertain/not sure yet 29% 32% Improved operational efficiency Improved customer experience APPENDIX 22
Figure 14 In-testing projects: Secondary benefits What would you consider the secondary benefit(s) of this IoT project your company is actively testing? (Select all that apply.) Other (please explain) Uncertain/not sure yet Improved production output quality Improved employee efficiency Improved production output quality Improved business awareness Improved customer data Improved customer experience Improved operational efficiency Cost savings 0% 5% 10% 15% 20% 25% 30% 35% Base: 109 APPENDIX 23
Figure 15 In-testing projects: Success factors How important are each of the following considerations to the ultimate success of this IoT project your company is actively testing? Project business value Data relevance Data integrity Platform security Data security Platform ability to meet future needs Platform ability to meet present needs Project cost of ownership Functionality of edge devices 0% 20% 40% 60% 80% 100% Base: 107 Not at all important Not very important Somewhat important Very important Critical APPENDIX 24
Figure 16 In-research projects: Stakeholder participation factors At what level have each of the following been involved in the active research of this IoT project? (Select all that apply.) Consultants IT staff IT leaders Operations team Line-of-business specialists Line-of business leaders C-level execs 0% 5% 10% 15% 20% 25% 30% 35% 40% Base: 68 Implementer Architect/specifier Technology approver Budgetary approver Primary sponsor APPENDIX 25
Figure 17 No organizational action taken: Why? What has deterred your company from pursuing IoT implementation? (Select all that apply.) Other (please specify) Unaware of the technology Security concerns We have insufficient internal expertise Line-of-business resistance Regulatory issues Management resistance No perceived business value Project would cost too much Immaturity of the technology IT resistance Base: 46 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% APPENDIX 26
Figure 18 Vertical industry Which of the following best reflects your primary market/industry? Manufacturing Other (please specify) Information technology Energy, power and utilities Education Government/public administration Construction Aviation/aerospace Warehousing, distribution and logistics Healthcare Agriculture Financial services Ground transportation Retail trade Real estate, rental and leasing Base: 612 0% 5% 10% 15% 20% APPENDIX 27
Figure 19 Company size: Employee count How many people are employed by your company, at all locations? 5,000 to 9,999 1,000 to 4,999 10,000 or more 100 to 999 4.6% 11.6% 20.5% 13% Base: 606 50.3% Fewer than 100 APPENDIX 28
Figure 20 Company size: Revenue Not applicable (government entities and other non-revenue-based organizations) $5 billion or more $1 billion to $4.9 billion $500 million to $999 million $100 million to $499 million What is the annual revenue of your company, in USD? 7.4% 6.1% 8.9% 11.6% 9.4% Base: 605 56.5% Less than $100 million APPENDIX 29
Europe Figure 21 Asia/Pacific Business location Where is your company located? (If your company has multiple locations, please select your primary location.) Latin America 10.4% Africa 7.6% 3.1% 2.6% Middle East 1.7% 74.5% North America APPENDIX Base: 604 30
Figure 22 Job function Operations/facilities Product management/r&d Which of the following most closely matches your job function? Marketing 9.7% 12.2% Base: 596 Purchasing/procurement 26.7% 21% 23.7% Other (please specify) Sales 5.0% 7% 6.9% 7.6% IT Finance 4.9% 2% 1.3% Business/organizational management Engineering APPENDIX 31
Other (please specify) President/ C-level Owner Figure 23 Job level Which of the following most closely matches your primary job level? Senior VP, VP 7.9% Supervisor 6.9% 15.4% 6% 5.2% 15.6% Base: 597 24% 19.1% Manager Director Individual contributor (no direct reports) APPENDIX 32