Welcome!

@ThingsExpo Authors: Liz McMillan, Zakia Bouachraoui, Yeshim Deniz, Pat Romanski, Elizabeth White

Related Topics: @ThingsExpo, Java IoT, @CloudExpo, @DXWorldExpo

@ThingsExpo: Blog Post

Critical Asset Insight Between #IoT and #BigData | @ThingsExpo #M2M #API #InternetOfThings

A theoretical looking glass capable of discerning the signal from the noise will find value nuggets

Through the Looking Glass: Critical Asset Insight and Transparency Increases Operational Efficiencies & Customer Confidence

A looking glass is a magical lens or portal through which things can be seen that are otherwise invisible. This is a perfect metaphor for the increasing challenge faced by businesses to find value hidden in the data they generate as well as data that they have access to. Value nuggets in data are often obscured by large volumes of data ("noise", if you will). The larger the data sets, the more obscured the value nuggets are. A theoretical looking glass capable of discerning the signal from the noise will find value nuggets that enable precise and timely reaction to situations, as well as proactive and prescriptive measures that result in real quantifiable benefits.

Erik Brynjolfsson[1] characterizes the benefits as a "data payoff." Results of his study of 179 large companies revealed that companies that used data-driven decision-making achieved productivity gains of up to 6%. Brynjolfsson further asserts that "a 5% increase in output and productivity is significant enough to separate winners from losers in most industries."

Seeing this payoff, more and more businesses are adopting a looking glass approach to understand the status of their operations and make on-the-fly positive improvements. Information and insights extracted from all data at rest and in motion enable new levels of efficiency for operations of all types and across broad geographic regions. Examples include distribution pipelines for water, oil and gas; global manufacturing operations; and transportation and logistics businesses.

Beyond internal efficiencies, businesses must also satisfy consumers who are becoming accustomed to transparency and have ever-increasing expectations of the companies they choose to support and do business with. Consumers are also accustomed to real-time responses and will overwhelmingly choose providers that deliver relevant information that is an integral aspect of an overall outstanding user experience.

Similarities between the Challenges and the Solutions to Big Data
The growth of data generation is due to a confluence of factors - Moore's Law and Metcalfe's Law. Powerful sensors embedded in many devices, including smartphones, tablets, and wearables[2], are proliferating because of declining size, lower cost, and increasing processing power, all attributable to Moore's Law. The ability of devices of all types to communicate through ubiquitous networks and make the information they capture and transmit available for analysis and storage is what Robert Metcalfe postulated in the early 1980s.

The same laws are at play regarding a looking glass solution, especially Moore's Law which is at the foundation of continuously increasing processing power that enables sophisticated in-memory analytics capable of executing in real-time. Continuous advancements in servers, storage, and software are the foundation for a looking glass, regardless of whether it is labeled as "artificial intelligence," "machine learning," or simply "analytics."

Impact of the Internet of Things and Big Data
Ongoing proliferation of low cost, battery-powered, sensor-equipped devices and ubiquitous communications are resulting in opportunities for businesses to peer through their own looking glass and see hidden value in their data that they can transform into actionable insights using advanced analytics. Businesses must peer through a looking glass to find insight hidden in all of their data.

Data volumes are increasing rapidly, especially data generated from sensors. The quantity and velocity of data generated is so great that not all of it is stored or analyzed. You can envision streams of data like water containing gold nuggets flowing into an ocean; data that is not analyzed while flowing and/or diverted for storage and subsequent analysis to extract the nuggets is lost forever. It is therefore imperative that data be analyzed while it is flowing so that you can now see your data, in motion, in real-time, to more deeply understand your situation in context.

This approach to analyzing data for insights is called situational intelligence and it lets you act quickly and confidently by providing a view of every situation from multiple perspectives. Situational intelligence also provides prescriptive suggestions and remedies, enabling you to proactively make beneficial decisions such as preventative maintenance.

When people think of big data they generally think of ecommerce and media properties: Amazon, CNN.com, Facebook and Google, to name a few. Such businesses capture every aspect of electronic end-user interactions with their properties.

A lesser-known source of big data is generated by electronic sensors that monitor the status of organizations' assets and operations. Manufacturing, mining, energy generation and/or distribution businesses, as examples, generate and capture massive amounts of data from their business operations. These industries and businesses capture data from physical assets, many of which are "smart," which is to say they have embedded sensors and are able to transmit telemetry data. Smart devices are replacing "dumb" devices; as an example many power utilities are replacing their usage meters with smart meters, obviating human meter readers from making recurring visits to read and record usage. In addition, new types of smart devices are being invented and deployed. Transportation and logistics providers generate and capture massive amounts of data from their business operations, especially in-vehicle telematics. Data from such devices is growing at an increasing rate, and much of it is neither captured nor analyzed.

Within the business and industrial sectors such smart devices are being referred to as an Internet of Things (IoT), or connected, devices. As noted above, organizations must embrace not only IoT, but the ability to harness the valuable information and insight they provide. Several interrelated technologies are required to derive not just insight, but at-a-glance actionable insight; key among those technologies are analytics capable of operating on very large data sets (aka big data) in real-time.

Increasing Your Operational Efficiency and Productivity
The challenge that businesses face is capturing, aggregating, and analyzing their data to find patterns, trends, clusters, anomalies - insights, if you will - that never before would have been found. Taking this a step further is to make those insights readily visible to the appropriate decision makers and/or to other systems and processes for real-time action. Greater throughput is an obvious advantage of widening or removing bottlenecks, especially in the case of automated machine-to-machine decision making. Another operational advantage and productivity enhancement is that your managers and staff will have at-a-glance assurance that everything is optimal and okay, and when that's not the case alarms and alerts will direct their attention accordingly. Depending upon the situation and the capabilities of the analytics, recommended actions and remedies may also be provided by the analytics solution.

A transformation of your business to this operating state and tempo will position your business for future success and avert competitive defeat or overall obsolescence. Benefits include streamlined internal processes, more productive field workers, the detection of unauthorized or rogue use of your resources, and greater availability of your plant, network(s), and physical assets. An example of this is predictive insights, which drives proactive maintenance to increase overall uptime that in turn assures production capacity and compliance with service level agreements and the like.

Consider the case of a large transportation logistics company. Knowing the exact location and use of its assets in the field will save millions of dollars each year. This company's field assets are taxed differently when they are on-road versus off-road, so having precise location and time-of-use information reliably streamed from in-vehicle telematics (without human errors) is essential. Analyzing that information enables reporting with never-before-possible granularity that eliminates rounding assumptions of the past, lowering their operating costs.

Enhancing Your Customers' Experiences
Bringing relevant real-time information forward in readily digestible formats to your end users and other stakeholders gives your business many opportunities to differentiate itself and realize your competitive advantage.

Imagine two airport shuttle services, one with in-vehicle telematics that provides current location and temperature inside the vehicle and one that does not. End users are more apt to choose a vehicle where they have a high confidence in an exact pickup time that is calculated based on the distance of the vehicle to their location and current traffic. The shuttle information is even more compelling and of greater impact to the selection of vendors if the end user is aware that the interior of the vehicle is a comfortable 72 degrees. As this example highlights, the user experience and interactions will increasingly include real-time information and insights from an organization's physical assets.

Another common example is parcel shipment and delivery. Consumers want to know when their purchased items or parcels have shipped, where they are now, and a reliable estimated time of arrival with as much granularity as possible (i.e., to within an hour). Such information and transparency between consumers and businesses is increasingly important to attract and retain consumers who have an ever-increasing palate of options to purchase and receive the items they need and want. If you think about it, sensors and ubiquitous communications make it possible to connect a parcel to a conveyance and to the person awaiting delivery.

Implementing Your Looking Glass
I am clearly an advocate of using data analytics to drive high-confidence business decisions. Moving in this direction generally impacts your entire enterprise, so I recommend a phased approach and the following steps to putting in place your own metaphorical looking glass.

As a first step I recommend your departmental leaders, including your IT team, be involved early in the process. The next step is to establish a vision of how your business will operate after becoming proficient at data-driven decision making. The vision should include explicit and measurable goals and corresponding use cases. If appropriate to your business operations your long-term vision needs to identify whether the ultimate goal is analytics-aided decision-making and/or fully automated decision-making (e.g., machine-to-machine decision-making).

Another critical early step is to identify all internal data sources and additional complementary external data sources that will be needed to support your decisions and goals. To ensure that your analytics program moves forward with little or no unanticipated delays, you will also need to assess data quality and data accessibility. An experienced analytics vendor can work with you to assure successful integration of data into your analytics program.

In addition, make sure the vendor and/or system integrators you choose have the capabilities and a track record of delivering and successfully implementing reliable and scalable enterprise analytics programs. Important capabilities to assess and require are: capabilities of the core product, extensibility of the analytics, professional services that includes data science, training, and support. If you anticipate extending your analytics program to multiple use cases, you should give strong consideration to a platform. In the case of an analytics platform, you should also favor a broad pallet of algorithms, the ability to easily add custom analytics, and a supporting ecosystem of plugins, developers and integrators.

To maximize early successes, I recommend to constrain your analytics project by choosing one or a small number of realistic and achievable goals and align the early phases of your implementation to what is necessary to achieve those goals. Build on your successes and momentum by incorporating more goals and use cases into your analytics program. Also make sure to review the program, including the vision, goals, phases, successes, lessons learned, and areas for improvement as widely as possible.

Summary
Value nuggets hidden in your data truly deliver a quantifiable "data payoff" too valuable to forego. Lagging or failing to find value nuggets and not using analytics to facilitate data-driven decision-making will place your company at greater risk of competitive disadvantage or obsolescence.

Situational intelligence empowers your staff and your company to act quickly, decisively, and confidently in any situation. Realizable benefits include increased productivity, increased customer satisfaction, and competitive advantage.

References

  1. Erik Brynjolfsson is the Schussel Family Professor at the MIT Sloan School of Management, Director of the MIT Initiative on the Digital Economy, Research Associate at NBER, and Chairman of the MIT Sloan Management Review. His research examines the effects of information technologies on business strategy, productivity and performance, Internet commerce, pricing models and intangible assets.
  2. Smartphones, tablets, and wearables typically include several of the following: an audio sensor (a microphone), a video sensor (a camera), position & motion sensors, a human pulse sensor, a temperature sensor, and a GPS location sensor.

More Stories By Paul Hofmann

As Chief Technology Officer at Space-Time Insight, Paul Hofmann, PhD, draws on over twenty years of experience in enterprise software, analytics and machine learning. He has held executive roles at BASF and SAP, where he was VP R&D, and conducted academic research at MIT, Technical University in Munich and Northwestern University. Most recently, Paul served as CTO for Saffron Technology.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
The challenges of aggregating data from consumer-oriented devices, such as wearable technologies and smart thermostats, are fairly well-understood. However, there are a new set of challenges for IoT devices that generate megabytes or gigabytes of data per second. Certainly, the infrastructure will have to change, as those volumes of data will likely overwhelm the available bandwidth for aggregating the data into a central repository. Ochandarena discusses a whole new way to think about your next...
DXWorldEXPO LLC announced today that Big Data Federation to Exhibit at the 22nd International CloudEXPO, colocated with DevOpsSUMMIT and DXWorldEXPO, November 12-13, 2018 in New York City. Big Data Federation, Inc. develops and applies artificial intelligence to predict financial and economic events that matter. The company uncovers patterns and precise drivers of performance and outcomes with the aid of machine-learning algorithms, big data, and fundamental analysis. Their products are deployed...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...
All in Mobile is a place where we continually maximize their impact by fostering understanding, empathy, insights, creativity and joy. They believe that a truly useful and desirable mobile app doesn't need the brightest idea or the most advanced technology. A great product begins with understanding people. It's easy to think that customers will love your app, but can you justify it? They make sure your final app is something that users truly want and need. The only way to do this is by ...
CloudEXPO | DevOpsSUMMIT | DXWorldEXPO are the world's most influential, independent events where Cloud Computing was coined and where technology buyers and vendors meet to experience and discuss the big picture of Digital Transformation and all of the strategies, tactics, and tools they need to realize their goals. Sponsors of DXWorldEXPO | CloudEXPO benefit from unmatched branding, profile building and lead generation opportunities.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Cell networks have the advantage of long-range communications, reaching an estimated 90% of the world. But cell networks such as 2G, 3G and LTE consume lots of power and were designed for connecting people. They are not optimized for low- or battery-powered devices or for IoT applications with infrequently transmitted data. Cell IoT modules that support narrow-band IoT and 4G cell networks will enable cell connectivity, device management, and app enablement for low-power wide-area network IoT. B...
The hierarchical architecture that distributes "compute" within the network specially at the edge can enable new services by harnessing emerging technologies. But Edge-Compute comes at increased cost that needs to be managed and potentially augmented by creative architecture solutions as there will always a catching-up with the capacity demands. Processing power in smartphones has enhanced YoY and there is increasingly spare compute capacity that can be potentially pooled. Uber has successfully ...
SYS-CON Events announced today that CrowdReviews.com has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5–7, 2018, at the Javits Center in New York City, NY. CrowdReviews.com is a transparent online platform for determining which products and services are the best based on the opinion of the crowd. The crowd consists of Internet users that have experienced products and services first-hand and have an interest in letting other potential buye...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...