by Stephanie Atkinson

Preparing your enterprise for IoT and automation in the workplace: Part 1

Dec 02, 2016
Big DataCloud ComputingHybrid Cloud

The first installment of a three-part series explores key findings, recommendations and business-critical areas to understand when planning, refining or implementing IoT systems

cloud computing data center
Credit: Thinkstock

Enterprise and industrial internet of things. Is your business ready? It can be very overwhelming when thinking about IoT for your business, especially because IoT is such a broad and all-encompassing term that encompasses various markets and technologies, and is even used for both consumer and business discussions.

Today, businesses need specificity, applicability and true business value discussions when speaking with technology vendors and partners. Even when my firm, Compass Intelligence, performs research in this area, we tend to be challenged daily with so much “fog” across vendors, carriers and even customers when discussing IoT. After attending multiple enterprise and technology conferences this year and speaking with businesses, I would like to sum up some key happenings, findings and wisdom that might help your business have better discussions as you plan for 2017.

Below are a few areas to explore and discover as you continue or begin your IoT journey:

  • Data analytics at the edge.
  • Leveraging real use cases and implementations.
  • What is actionable data?
  • Complexity brings fear in business decisions.
  • IoT investment, fear of high expenses.
  • Legacy challenges.
  • Securing IoT and where the cloud plays a role.
  • In comes artificial intelligence and cognitive learning.

For Part 1 of this discussion, I will address the first three bulleted items. In late December, I will continue with the next three items.

Data analytics at the edge

Fog computing (a concept developed by Cisco) and edge computing have become critical needs for enterprises as we have uncovered and discussed with vendors and companies implementing connected solutions, automating operations and connecting devices. This need is all about where and how we  process, compute, store and analyze data and application services we are collecting from sensors, machines and other connected objects. Do we really need all data pushed offsite to a cloud-based data center? No, and in fact the growth of data we are collecting and storing is really not able to keep up with the bandwidth we have today.

So in comes fog or edge computing. Fog computing is a distributed computing approach where application services may be controlled at the network edge in a smart device and some application services are controlled in a remote data center or cloud environment. Fog computing allows a considerable amount of processing to occur at the edge of the network in a smart router or other gateway device. See also Mobile Edge Computing (developed by ETSI). The ability to process and analyze data at the edge becomes even more important as it reduces latency, provides for real-time analytics and quick decision-making, and works best where we have a high volume of sensor or connected devices (dense IoT networks). Specific industries where this makes the most sense are those in industrial verticals, smart cities (transportation, infrastructure), intelligent buildings, oil and gas or energy, and others. Lastly, security at the edge is a must and should not be overlooked by businesses. (Explore solutions from Cisco, Aeris, Camgian, Flutera, note some are hardware and some platform solutions)

Leveraging real use cases and implementations

The best and most effective way for businesses and decision-makers to understand the value proposition of the internet of things is to evaluate, explore and review real-live use cases, actual implementations and hands-on feedback for best in class or benchmark case studies. The broadness of the applications makes this a challenging factor for different industries to understand how they can leverage these same technologies in their own industry. For example, how does it save money (ROI, TCO), increase efficiencies, improve customer service or customer experience, improve quality, reduce downtime, etc.? As challenging as IoT is, it is even more of a challenge to justify the investment and provide trackable metrics to demonstrate value to the executive team. Keep in mind, many IoT projects are undertaken outside of the IT department, which means it can be even more challenging to bring together information technology (IT) and operational technology (OT) for implementation. In fact, some decisions may even be made by marketing or customer experience teams, as the application may be to improve the overall customer experience for that business. Use cases provide additional color and context, and showcase applications that can be horizontal and work across industries and provide ideas for other industries looking to automate. Attending conferences and pushing your technology vendors/partners to walk you through examples may be the most valuable ways to understand value proposition for IoT. At IoT6 Exchange (a conference held in San Antonio in November) we heard real live use cases from Clearblade (customer: Stanley Black and Decker), VMware/Airwatch (customer: Coca Cola), HPE (customer: Flowserve).

What is actionable data?

A nice theme echoed all year is “We can’t collect data for the sake of just collecting data.” Some businesses are becoming overwhelmed with the thought that we need to collect all data from a device, machine or smart object. First of all, this would not be productive or effective for the network because of bandwidth concerns. Secondly, without actionable data or data that can be used to make a decision, provide an alert, trigger an important action, secure an asset, or provide some other relevant action, the data may not be important to collect. Thinking strategically about your entire company and industry ecosystem should be the first step. We call this industry ecosystem mapping. Understanding what operations, processes, software/applications, machines, computers, devices and information is being exchanged internally and externally are being performed in your business is crucial. This will help your organization understand what is already being collected today, how the data should be accessed/stored/processed, what should be collected that is not being collected yet, and how best to leverage data and turn it into actionable intelligence. After the ecosystem review is complete, your teams should be well prepared to speak with technology vendors and partners about your overall data needs and incorporate that into your IoT strategy.