Internet of Things (IoT) Meets Big Data and Analytics:

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1 March 2015 Sponsored by

2 Introduction The Internet of Things (IoT) and Big Data have each made press headlines and continue to be board-level priorities. The intersection of IoT and Big Data is a fascinating area of innovation with tremendous scope for business impact. From industrial sensors to vehicles to health monitors, a huge variety of devices connect to the Internet and share information. At the same time, the cost to store data has dropped dramatically while capabilities for analysis have made huge leaps forward. But are these connected devices actually gathering usable data? What are the challenges in storing and analyzing huge amounts of real-world information? Does improved data analysis benefit IoT projects? The following report, sponsored by ParStream, is based on a survey of technology and business professionals with responsibility for IoT projects. Participants included Technology stakeholders (development, IT operations, and systems integrators) as well as Business stakeholders (business owners, product managers, program managers, and business intelligence). The goal of the survey was to understand experiences and impacts of using the data captured by the devices that make up the Internet of Things. Key Findings IoT projects vary widely but all have challenges 53% are using IoT projects to optimize existing businesses; 47% as a strategic business investment Target audiences for IoT solutions include consumers (42%), business (54%) and internal use (51%) 96% have faced challenges with their IoT projects IoT not delivering full potential because of data challenges 86% of stakeholders in business roles say data is important to their IoT project Only 8% are fully capturing and analyzing IoT data in a timely fashion 94% face challenges collecting and analyzing IoT data Better IoT data collection and analysis would deliver more value 70% say they would make better, more meaningful decisions with improved data 86% would increase the ROI of their IoT investment Detailed Findings IoT projects vary widely When any device has the potential to be connected, the possibility for impact is immense. Opportunities to deliver business value range from truly innovative devices that create completely new markets and business models, to the more mundane but high value solutions that deliver cost and efficiency benefits by simplifying existing processes. We asked participants to classify the business goal of their IoT project in one of these two ways: Optimize existing business - increase employee productivity, reduce cost of operations, improve customer experience, etc. Strategic business investment - open new market opportunity, enable new business model, etc. Sponsored by

3 Interestingly, we found our participants were split down the middle. Just over half (53%) described their IoT project as optimizing an existing business process or function, while just under half (47%) characterized themselves as working on an IoT project that was a strategic business investment. Which of the following best describes the primary business driver of your IoT project? Strategic business investment 47% Op#mize exis#ng business 53% There were some contrasts in the way different participants characterized their IoT project business drivers. Technology professionals were more likely to describe their projects as business optimizers (73%), where business stakeholders were more likely to be involved in strategic business investments (68%). IoT projects designed to optimize existing business functions are slightly ahead in their lifecycle. Participants whose IoT projects were already in the hands of users, either fully released or in a controlled release, were more likely to describe their projects as optimization (58%). IoT projects also cover a wide variety of target users. While IoT buzz has often centered on consumer-centric devices like smart door bells, and home monitors that customize lighting and music to their occupants, less than half of the IoT stakeholders in this survey were working on IoT projects aimed at consumers (42%). More were working on IoT solutions for use by businesses (54%) and internal business use by employees or partners (51%). 60% 40% Who are the target users for your IoT project? 54% 51% 42% 20% 0% Consumers (B2C, individuals) Businesses (B2B, companies) Internal business use (employees or partners) Page 3

4 One third of IoT projects have quantifiable success metrics IoT projects are still in early stages, and many projects do not have hard measurements to track success. One third (33%) reported that they will track their success using quantifiable metrics. Slightly fewer (29%) do have documented goals for success, but these goals cannot be quantified. The most common IoT project evaluation criteria reported by participants is merely to gain experience (38%). How will you evaluate the success of your IoT project? Our objecave is to explore our opaons, so the process of learning will be our business success 38% We have quanafiable metrics to track success 33% We have documented goals, but they are difficult to quanafy 29% What aspects of IoT projects face many challenges Any new technology brings challenges, and IoT projects have been no exception. Almost all IoT stakeholders (96%) report facing challenges. The main challenges reported are around business processes and policies (58%) followed by user adoption of new technology (51%). Several participants took the time to document Other challenges that they face. These included identifying and selecting appropriate platforms, pace of change, lack of standards, and a lack of understanding and consistency across internal and external stakeholders, including vendors. What aspects of your IoT project have been most challenging? Business processes or policies (e.g. privacy) 58% User adopfon of new technology 51% Timely collecfon and analysis of data Sensors or devices 41% 40% Other We have not faced challenges with our IoT project 4% 6% 0% 10% 20% 30% 40% 50% 60% 70% Page 4

5 Data is captured, but not used fully The majority of IoT projects do involve data collection, but very few are fully leveraging the opportunity that data provides. Only 17% of our survey participants indicated that they do not capture data as part of their IoT projects. While the vast majority, 83%, are collecting data, only a very small number (8%) report that they are making the most of their data by fully capturing and analyzing data in a timely fashion. More than half of participants (58%) are making an effort and are doing some analytics, but they know they can do better. What level of data capture and analy2cs does your IoT project deliver TODAY? We are fully capturing and analyzing all data in a <mely fashion 8% We don't store IoT data 17% We capture and store data, but we don't analyze it 17% We do some analy<cs, but want to do be=er 58% The 17% of participants who indicated they don t store data were asked why. Most of these participants simply were not far enough along the path of their IoT project to be capturing data yet, but they did have plans to implement capabilities. In addition, some IoT stakeholders reported business issues around confidentiality of the data which created privacy issues that prevented collection. IoT data is important, especially to business stakeholders Those who did store IoT data consistently reported that collection and analysis was important to the success of their projects. Only a tiny number of participants (1%) indicated that their IoT data was not important, and that number did not include any business roles. Among all IoT stakeholders, most (77%) indicated that data collection and analysis was important. This number was even higher among the business stakeholders surveyed, with 86% characterizing IoT data as important. How important is data collec1on and analysis to your IoT project? All 77% 22% 1% "Business" 86% 14% 0% Important Nice- to- have, but not vital "Technology 68% 31% 1% Not important 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% n = store IoT data Page 5

6 Those who store IoT data do tend to store it for a long period of time. The vast majority of participants, 89%, reported that IoT data was stored for more than a week. This included almost half (47%) who store their IoT for more than a year. 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% How long do you store your IoT data? 47% 24% 18% 7% 4% 0% Less than one hour Less than one day Less than one week Less than one month Less than one year More than one year n = store IoT data Challenges are faced at all stages of IoT data collection and analysis Most IoT stakeholders, 94%, report challenges related to data capture and analysis. Any data project includes multiple steps: capturing the data, analyzing the data, and acting on that analysis. IoT projects are no exception. Survey participants reported facing challenges in each of these steps including difficulties capturing useful data (36%), having too much data to analyze effectively (44%), and not knowing what questions to ask (27%). What challenges do you face in collec2ng and analyzing the data in your IoT project? Difficult to capture useful data 36% Data is not captured reliably 25% Data is captured too slowly to be acconable Too much data to analyze effeccvely 19% 44% Data capture Analysis capabilices are not flexible enough to ask the quescons we want 30% Data analysis Data is analyzed too slowly to be acconable We re not sure what quescons to ask Business processes are too rigid to allow us to act on the analysis 24% 26% 27% Acting on analysis Other We have no challenges 6% 7% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Page 6

7 Other challenges with data collection and analysis reported by participants were varied. Issues included technical challenges such as dealing with unexpected data, data that is out of spec, data that is not in a usable format, and correlating with data from other sources. Some process centric challenges reported were including training users on how to use the data, dealing with information that belongs to siloed organizations, and developing new business models to leverage analysis. Ease of use limits data capture more than cost Interestingly, while cost is often a limiting factor in many technology decisions, for IoT stakeholders, ease of use appears to be a more pressing issue than cost. More participants (76%) say they would collect and store more data if it were easier than those who said they would if it were free (68%). If collec(ng and storing IoT data was EASIER, would you collect and store more? If storing addi=onal IoT data was FREE, would you collect and store more? No 24% No 32% Yes 76% Yes 68% Better IoT data capture would be beneficial IoT stakeholders do think better IoT data capture would have a positive impact. The majority, 92%, reported that they would see benefit if they captured and stored their IoT data faster and more cost effectively, with the ability to make better decisions the most frequently expected benefit (70%). If you were able to capture and store IoT data faster and more cost effec6vely, what benefits would you expect? Make beber, more meaningful decisions 70% Make decisions faster 53% Make more decisions 27% Other There would be no benefits 6% 8% 0% 10% 20% 30% 40% 50% 60% 70% 80% Page 7

8 Better analytics would increase ROI of IoT projects When specifically asked about the business impact of better analytics, most IoT stakeholders (86%) reported that faster and more flexible analytics would increase the ROI of their IoT investments. This included 44% that believed ROI would increase significantly as a result of better analytics. IoT stakeholders in business roles were even more likely to report that better analytics would deliver ROI with 92% saying that ROI would increase, including 58% that believed the ROI increase would be significant. What would the business impact of faster and more flexible analy8cs be on your IoT project? All 14% 42% 36% 8% No impact "Business" 8% 34% 46% 12% We would slightly increase ROI We would significantly increase ROI "Technology" 15% 57% 24% 4% We would massively increase ROI 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Survey Methodology and Participant Demographics In January 2015, technology and business stakeholders with responsibility for Internet of Things (IoT) projects were invited to participate in an online survey on the topic of leveraging data captured by the devices that make up the Internet of Things. Participants were asked a series of questions about their role in IoT projects, as well as business goals, challenges, and use of data. Business intelligence or data analy6cs 14% Development or QA 20% Business, 48% Technology, 52% Business stakeholder 18% Role in IoT project Product or project manager 16% System integrator or ISV 4% IT produc6on opera6ons 28% Page 8

9 A total of 203 individuals participated in the survey. All had professional responsibility for IoT projects. Participants represented a wide range of geographies, company sizes, role, and vertical industries. EMEA 19% Region APAC 7% External consultant 10% Invididual contributor 30% Job Func)on Execu&ve 29% Planning a pilot 17% S:ll in concept phase 22% Status of IoT Project Fully released 12% Controlled release 17% AMER 74% Team manager 31% Early stage pilot 32% About Dimensional Research Dimensional Research provides practical market research to help technology companies make their customers more successful. Our researchers are experts in the people, processes, and technology of corporate IT and understand how corporate IT organizations operate. We partner with our clients to deliver actionable information that reduces risks, increases customer satisfaction, and grows the business. For more information visit. About ParStream ParStream is the industry s leading IoT analytics platform company. The ParStream analytics platform was purpose-built for scale to handle the massive volumes and high velocity of IoT data. ParStream s platform delivers a new breed of analytics for the enterprise, such as Geo-Distributed Analytics which enables analytics at the edge. ParStream has earned multiple accolades including the M2M Evolution IoT Excellence Award, CIO Magazine #1 Big Data Startup, and Gartner Cool Vendor. ParStream is based in Silicon Valley, online at and on Page 9