How the IoT Will Impact Enterprise Analytics

IoT devices are just about everywhere, in cities, on oil rig, and on our wrists. They're impacting virtually every industry, and their growth is outpacing organizations' ability to make the most of that data.

To give you an idea of scale, IDC expects global IoT spending to reach nearly $1.4 trillion by 2021, up from $800 billion in 2017. The IoT is all around us, in many cases fading into the backgrounds of our homes and lifestyles, all the while generating massive amounts of data. The trick is driving value from that data.

The Balance of Data is Shifting

Over the past decade, we've witnessed several shifts in enterprises' ability to deal with data. While different companies and industries are at different stages of maturity, we've seen and continue to see analytics evolving, whether it's adding unstructured analytics capabilities to structured analytics, third-party data sources to our own, or IoT data to enterprise data. Slowly but surely, we've been seeing the balance of data shift from internal data to external data, particularly as more IoT devices emerge.

Edge analytics helps separate meaningful data from all the noise, which usually means identifying, and perhaps reacting to, exceptions and outliers. For example, if the temperature of a piece of industrial equipment rises beyond a threshold, maintenance crews may be alerted, or the equipment might be shut down.

Organizations attempting to manage IoT data using their traditional data centers are fighting a losing battle. In fact, Gartner noted that the IoT is causing businesses to move to the cloud faster than they might move otherwise. In other words, when so many things are happening in the cloud, it makes sense to analyze them in the cloud.

Data and Analytics Strategies: Top-down and Bottom-up

The sheer amount of data organizations must deal with increases greatly with the IoT, and there are still philosophical debates about how much data should be kept and how much data should discarded. Gartner strongly advises its clients to be smart about IoT data, meaning that one should not save all the data hoping to drive value from it in the future, but instead focus on strategic goals and how IoT data fits into that.

We often hear how important it is to align analytics efforts with business goals. At the same time, we also hear how important it is to uncover unknown opportunities and risks simply by allowing the data to speak for itself. Some of the most sophisticated companies I've talked to over the last several years are doing both, with machine learning identifying that which was not obvious previously. In Gartner's view, "data and analytics must drive business operations, not reflect them."

One major challenge organizations face, practically speaking, is operationalizing analytics -- with or without the IoT. The core problem is moving from insights to action, which can't be solved completely with prescriptive analytics. It's a larger problem that has to do with company culture, stubborn attitudes and the very real challenges of integrating data sources.

Meanwhile, some organizations are pondering how they can use the IoT to improve customer experience, whether that's minimizing transportation delays, improving environmental safety or otherwise eliminating friction points that tend to irritate humans. Humans have become fickle customers after all, and each touch point can affect a brand positively or negatively.

For example, Walmart placed kiosks in some of its stores that retrieve online orders, scan receipts and trigger the conveyor belt delivery of the items a customer purchased. The kiosks address a customer pain point which is walking all the way to the back of the store and waiting several minutes for someone to show up only to be told the order can't be located.

Now think about what Walmart gets from the kiosk: trend data about customer use and experiences that may impact staffing, inventory management, marketing, supply chain. Clearly, the data will also indicate whether the kiosk idea is ultimately a good idea or a bad idea.

In the pharmaceutical industry, GSK has been working with partners to develop smart inhalers that track prescription compliance and dosing. The data helps inform research, and it also has value to doctors and pharmacies.

Similarly, enterprises can use IoT data to develop predictive models that help improve business operations, logistics, supply chain and more, depending on the nature of the sensors and the device.

Is Your Organization Integrating IoT Data?

What kinds of IoT devices does your company use? Has the data been integrated with other data so it can be analyzed in some sort of departmental context? What challenges have you faced? What advice do you have for others? We'd love to hear about your experiences in the comments section.

Lisa Morgan, Freelance Writer

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.

What Data Analysts Want to See in 2018

Is the enterprise itself getting in the way of achieving results from analytics insights? Here's a closer look at what organizations can do to get out of the way of analysts.

How Today's Analytics Change Recruiting

HR analytics aren't mainstream yet, but they're gaining traction because human capital management is a competitive issue. From recruiting to employee performance and overall HR operations, analytics will have an increasing impact on companies and individuals.

Re: Deluge of Data
  • 12/4/2017 11:55:43 AM

While as noted there is "still philosophical debates about how much data should be kept and how much data should discarded," I wonder if huge collectors of data such as Amazon and Google keep literally everything becsause they can or if even those outfits let go of some things collected figuring there's not use for the data.

Re: Deluge of Data
  • 12/1/2017 12:27:40 PM

Seth, I'm with you on this. Regulatory measures are reactive to actions already taken. It's not enough to merely apologize after bad deeds and expect to be left alone on your word to be good going forward. Example is uber amongst many.

Re: Deluge of Data
  • 11/30/2017 11:31:20 PM

This is why I believe in regulation.  Businesses say regulation is costly and a burden and it is.  But in almost every case, especially with financial companies, when companies promise to be good they don't.   

Re: Deluge of Data
  • 11/30/2017 11:35:10 AM

Seth, profit or greed if you will is the road map, and we know well that they know no clearly marked boundaries. Pushing the envelope is the core operating procedure.

Re: Deluge of Data
  • 11/30/2017 11:29:27 AM

Lyndon, the infamous unintended consequences is being played out with IoT. That starry eyed wonder started on a not well defined journey void of any guardrails or road map. Wild adventure!

Re: Deluge of Data
  • 11/30/2017 6:39:39 AM

Rbaz writes that ...

... the rules of the road are being written as we drive when it comes to all this data. I'm afraid that the boundaries or lack of, is being set by the people gathering the data. So profits will guide the journey.

I would say: profits along with other motivations. I think back just a few years when IoT was being portrayed with starry-eyed excitement as simply a major new advance in convenience. Now it's evident that some awfully nefarious interests are at work out there that are doing their best to exploit some extremely intrusive and dangerous vulnerabilities. 

In a sense, the "rules of the road" are sort of writing themselves, and our society is just at the starting line of that road.


Re: Deluge of Data
  • 11/30/2017 2:14:56 AM

@rbaz.  You touch on an important point about the boundries being set by those collecting the data.   However, there doesn't seem to be any.  The ony boundries we will have are those that are set by ourselves. 

Re: Deluge of Data
  • 11/29/2017 5:42:48 PM

Seth, the rules of the road are being written as we drive when it comes to all this data. I'm afraid that the boundaries or lack of, is being set by the people gathering the data. So profits will guide the journey.

IoT in public transport
  • 11/26/2017 3:04:58 PM

In her blog post Lisa asks

What kinds of IoT devices does your company use? Has the data been integrated with other data so it can be analyzed in some sort of departmental context? 

As I've reported in several previous articles published on A2, IoT is now used extensively in public transportation, both in urban transit systems and Amtrak's intercity rail passenger operations.

Regarding urban transit, in my article "Public Transportation Moves With Analytics" (12 July 2012) I summarized a number of functions such as automatic passenger counting, automatic vehicle location, automatiuc fare collection, and various passenger information features. These and more are now all typically linked via IoT, and the number of IoT-linked operations continues to expand.


Deluge of Data
  • 11/24/2017 11:03:43 PM

This makes me think of all the data provided by Google or Amazon's Alexa.  It's a marketer's dream come true of actually being able to be in someone's house and observe what they are doing.  Though Amazon and Google say that the device is only activated with a key word, anyone can go to their Google account @ myactivity, and listen to tons of recording from their cellphones that they did not initiate.

Amazon is considering allowing delevopers to have access to these conversations.

Compaines are lining up to get this data and there are consultant companies such as Epsilon's Data Design that are specifically targeting these needs.