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The Internet of Things: The connecting of “dumb” items and the creation of big data

The Internet of Things: The connecting of “dumb” items and the creation of big data

by | Dec 17, 2014 | Big Data, Blog, Data/Analytics, Internet of Things

the internet of things

The Internet of Things (IoT) is ubiquitous.  Because of this it can seem abstruse. Puneet Mehta does a great job of putting the concept in layman’s terms:  “[A] plethora of “dumb” objects becom[ing] connected, sending signals to each other and alerts to our phones, and creating mounds of “little data” on all of us that will make marketers salivate.”

The mounds of data created by the advent of the IoT does not just make marketers salivate.  Gartner predicts that the IoT will add $1.9 trillion in value to the economy by 2020.  Looking ahead, Cisco estimates that the IoT will create over $14 trillion in value over the next 10 years.

In 2003 there were 500 million connected devices.  Cisco estimates that this number will increase to 50 billion by 2020.  Morgan Stanley believes this number will be higher – it estimates there will be 75 billion IoT devices by 2020.

“Dumb” objects are becoming connected; the physical and digital worlds are converging.  Mounds of data are being collected.

IoT and Big Data

Mukul Krishna, from Frost & Sullivan, presented a simple incremental view of the relationship between the IoT and big data.  In short, IoT devices can be thought of as data sources.  These data sources generate an incredible amount of data – much of which was previously not accessible. The information and insights from big data allow for better decision-making.

the IoT and big data

The amount of big data created each day in 2012 was 2.5 exabytes (2.5×1018).  In 2014 the amount of data were created each day was 2.3 zettabytes (2.3×1021),

An IDC forecast shows that the Big Data technology and services market will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017 – or at about six times the growth rate of the overall information and communication technology market.

The need for a plan

McKinsey & Company offer sage advice: put a plan in place.

The payoff from joining the big-data and advanced-analytics management revolution is no longer in doubt. The tally of successful case studies continues to build, reinforcing broader research suggesting that when companies inject data and analytics deep into their operations, they can deliver productivity and profit gains that are 5 to 6 percent higher than those of the competition.  The promised land of new data-driven businesses, greater transparency into how operations actually work, better predictions, and faster testing is alluring indeed.

But that doesn’t make it any easier to get from here to there.

So how does one get from here to there?

The answer, simply put, is to develop a plan. Literally. It may sound obvious, but in our experience, the missing step for most companies is spending the time required to create a simple plan for how data, analytics, frontline tools, and people come together to create business value. The power of a plan is that it provides a common language allowing senior executives, technology professionals, data scientists, and managers to discuss where the greatest returns will come from and, more important, to select the two or three places to get started.

What impact has the IoT and big data had on your company?  Does your company have a plan in place?

Put decision quality data in the hands of decision makers

by | Jul 27, 2012 | Blog

It’s safe to say that the clients I engage with fall into two categories when it comes to business data; those that are drowning in it and those that ignore it altogether. The ones that are drowning in data know all the relevant facts that keep them out of trouble with their Boards or their senior executives, but struggle to tell you what really drives their business costs or profits. The ones that ignore the data are the savvy veterans that rely on their historical win / loss records in their business, but ask them to change course or innovate, and they are like fish out of water.

Chances are you’ll fall somewhere close to those two camps, and for some time, I did as well. It was then that I realized that tracking data for the sake of “tracking” was a waste of time for me and for my teams. However, there is data that should be relentlessly tracked and used in all of your decision processes. I call this data, “Decision-Quality”. This is the data you track that drives your business strategy and execution.

Decision Quality data goes beyond the traditional Profit / Loss packages that are churned out every quarter and disseminated to your business chieftains.  Decision Quality Data sets are the building blocks and the levers of your business. Examples of Decision Quality Data are areas of your business that can be affected by the execution of your employees. Put simply, your sales employees may not be able to directly affect your finance treasury function, but working together with your finance team, they CAN effect cash flow by selling credit-worthy customers, cutting better financial deals, and when necessary, helping in the collection process. The same can be said of your purchasing professionals teaming with distribution leaders and finance team. This team can coordinate at the front line to cut costs and reduce inventory spend by developing inventory and financial metrics that matter to them and the company overall. By working in concert, they have the ability to solve the problems that arise and avoid pitfalls in real time instead of reacting when the quarterly metrics come out.

Quite frankly, if you are collecting and looking at data, but not taking action as the result of it, STOP. You won’t miss a thing and your team will thank you for saving them time to spend on more productive activities. Don’t fall into the data-cycle-trap dictated by data that is tracked on a calendar basis for the sake of tracking. Ask your teams what data they need to be effective, and simplify the way for them to get it in near real time. Once this type of data is in the hands of a cross functional team of front line managers, task them with the needed improvement and watch them make dramatic impacts in your overall business performance and customer experience, and in turn, your profits.   The results will be better and more sustained than if you drove them with a mandate from the top because these managers live and breathe in the environment that created the data in the first place. Their cross functional nature and familiarity with the issues are a winning combination. Give them the data and the direction and watch your teams win.