The Internet of Things: Our Bright Future or Inevitable Downfall

Post written by Blake W., Management Consultant at Ideaca. Read more on his blog: Blake Watson.

The Internet of Things (IoT), essentially a future-focused concept where everyday devices connect and communicate data in an intelligent fashion is a highly contested topic. Will it mark the beginning of a new era in our civilization or a catastrophic detriment to the world as we know it? Skipping over the possibility of our technology becoming self-aware and “terminating” us, these two polar opposites are often portrayed in the discussion of this topic. This post will broadly summarize the IoT and discuss the positives and negatives in relation to our daily lives.

So what is the IoT? It is a term that has been vaguely used since the 1990’s and has gained traction since its initial public proposal by Kevin Ashton in 1999. It is a term that suggests a heavy increase in device-to-device and device-to-Internet connectivity. By equipping these devices into a worldwide network of miniscule identification devices the IoT could transform our daily lives.

Is this interconnectivity even possible? Simply put, yes. Technology is growing at a rapid pace, confirming Moore’s Law, wherein Gordon E. Moore’s observed that the transistors, and thus the processing power of our devices, double approximately every two years. Although many have debated the staying power of this observation, the exponential potential of this theory is astounding. If the past few decades are any indication, the IoT is a highly probable (and sometimes frightening) reality.

As mentioned before, the IoT could transform life as we know it. A simple scenario: You get home from a busy day at work. Monitors in your home identify you and let you in. Immediately, the room taps into a wealth of your personal information and preferences…climate control, music, lighting, and digital décor. These sensors may even be able to determine what you want for dinner and start preparing it for you based off of what is in your refrigerator. Some of these devices are already available through “smart” technology. Within the next 20, the possibilities are endless.

THE GOOD:

For the individual, the IoT integration arguably increases our standards of living. No longer are we plagued by menial tasks that take up our days. The IoT essentially frees up time and energy that could be better spent productively or recreationally. It doesn’t necessarily mean that as a collective we will be healthier, happier individuals. However, we will have more opportunity to achieve this lifestyle.

From the business perspective, greater analytic capabilities are accessible to management and supervisors. Asset tracking, inventory controls, and financial drilldowns are far more accurate. Location services, automation, and device interconnectivity eliminate a great deal of the “guess-timation” involved in these operations. Sectors such as consulting, financial services, and even health could benefit greatly from these advancements.

Businesses also have access to a huge amount of data. Big Data will be a simple task compared to the vast amount of information that corporations will be able to collect from client usage and habits. We will have to start considering XXXL Data as opposed to Big Data. Billions and even trillions of source data will give business owners the tools to minutely tailor their products and marketing to individuals in the most literal sense of the word.

THE BAD:

The IoT has a dark side to it. Many people feel a sense of unease when they consider the privacy concerns the IoT imposes. If you are the slightest bit afraid of “Big Brother”, then the IoT is not for you. The amount of information that can be collected by governments and corporations through the billions of personal, business, and home devices is astounding. These devices sometimes know more about you than you do.

Another hot topic at the moment is job security; for low income earners, the IoT could make things especially tough. A number of unskilled tasks (and even some higher level analytics) might easily be replaced by a network of devices connected to the IoT.

Another concern is the effect that this new world order may have on our physical health. When all of our devices are communicating, making decisions, and essentially managing our lives for us, the opportunity to become complacent with that level of comfort is tempting. The World Health Organization estimates that over 65% of the world’s population currently lives in countries where obesity kills more people than being underweight. This upward trend isn’t expected to slow down anytime soon, especially with the continued introduction of technology that makes our lives even easier.

OVERALL:

Although there are many negatives that could affect reception of the IoT, it is my belief that reactions will be mostly positive. Although some aspects of these new technologies are to our detriment, there is a great deal of benefit that can come from an increased awareness of the IoT. As younger generations are brought up with modern day technologies, we may begin to see society move away from a privacy-centric culture. This shift would effectively reduce public outcry for greater privacy rights in this changing environment.

Although malicious Internet hackers and identity thieves may pry on the wealth of information available, we are facing no greater threat in the future than we are now. Security safeguards are in place and continue to develop. At the same time, data thieves are growing their methods for subverting such safeguards. This struggle for access and security will continue with no real definitive end in sight. Therefore, data security should not be considered within scope of this discussion.

The main problem moving towards our ideal vision of the IoT is that it will depend heavily upon data sharing and corporate cooperation. Think of all of the different products in your home… appliances, personal devices, clothing, and climate control. Seamless integration is necessary to ensure the IoT is able to function effectively in your daily life. If your devices cannot access the personal information it needs it will not function properly. It is hard to imagine companies (For example, Apple and Samsung) sharing customer data and integrating their products out of the box. Cooperation will be mandatory and it is something that companies will have to be overcome as we move forward with the IoT.

As briefly mentioned above, consulting firms such as Ideaca Knowledge Services will benefit greatly from the wealth of information available to them. The greater availability of information resources will allow their consultants to better assess client needs. Having clear needs from both the client and end consumer is essential. Better data means better solutions and ultimately better deliverables.

Whatever your take is on the IoT, there are a lot of variables to take into account. The changes that it will bring to our society are truly hard to imagine 20 years out. For good or for bad, the world is growing and developing towards the IoT. Will we try to hold on to our present state of technology or embrace these changes when they come?

The Future (IS) Worker

Post written by Chris S., Project Manager at Ideaca. Read more about project management on his blog: The Outspoken Data Guy.

If the lines have not already been blurred, they will be…Over the next 10 years business and IS work will undergo a major transformation, largely driven by the Cloud and Data Analytics.

In the next 10 years, internal IS staff will act solely as advisers and managers of cloud services.

As more and more businesses embrace cloud services, IS will be called upon to act as advisers to ensure that these services are managed as efficiently as possible. As a consequence, this will push IS Governance further into the limelight. For years IS has had the notion of charge-back to the business to help manage costs and allocate them to those that use services. This approach has been mired in political push back and logistical challenges around how this would be done in a fair and equitable manner. As we move towards a “Pay for Usage” model in the cloud, these costs will be far easier to allocate back to those that use and hence IS will get a more accurate picture of costs of services and a far better allocation model.

This likely will not sit well with legacy users but the notion of “pay for usage” is so common place with Generation Z that this will be a virtual non issue. With this political hurdle out of the way, the focus can shift to more efficient use of IS resources and to ensure that businesses are getting value.

It is hard to argue with the value of using cloud services. At present there are the usual security and performance questions but over the next few years these concerns will be addresses and we will all have our heads in the clouds.

The new beast - hybrid IS and Business Person

Who is the future (IS) worker? And what skills will they need to bring to the table?

In my opinion the niche where people will have the most success will be with a hybrid of IS and business skills. There is no real debate that the world is increasingly becoming more data driven and the ability to turn data into actionable insights will become more in demand. So what does that mean? It means that workers will need to have 2 very key kills:

a) A deep understanding of the business and b) the ability to analyze data and derive insights.

This phenomenon, coupled with the cloud will allow Business Intelligence services to move closer to the business with IS once again acting as advisers, which is where BI needs to be currently in organizations. Unfortunately it gets stuck into an unnecessary tug of war between IS and the Business.

Bottom line: Business users will have to become more technically savvy as is articulated in Thomas Davenports “Keeping up with the Quants.”

Business Intelligence is weaving its way into our daily lives - it is the age of data.

Building on the above, on a daily basis we are increasingly faced with data that we use to guide our actions, personal or otherwise. Real time traffic signs that tell us how long it takes to get somewhere, integrated budgeting software in our banking site that monitor our daily spending and alert us to certain conditions that we are interested in and feedback about restaurants that we may want to have lunch at. These are just a few examples of where data is used daily to guide our decisions.

 Bottom line: Data and analysis are becoming a way of life and will continue to forge its way into the mainstream.

Is Big Data Only About…Big Data?

Post written by Wade W., BI Consultant at Ideaca. Read more about BI on his blog: Pragmatic Business Intelligence.  

If nothing else, IT is all about buzzwords, and “Big Data” is one of the new arrivals to the party.
It is, however, a descriptive one. “Big Data” evokes images of enormous relational databases, providing analytical (or operational) reporting.

Big Data is not only about size however. Rather, it refers to attributes of the data that together challenge the constraints of a business need or system to respond to it. Those attributes can include any or all of attributes such as size/volume (of data), speed (of generation), and number and variety of systems or applications that simultaneously generate data. Another thing that is unique about Big Data is how it varies in structure. Elements of “structure” would include the diversity of its generation (eg. Social media, video, images, manual text, automatically generated data, such as a weather forecast, etc), information interconnectedness and interactivity.

I heard somewhere a thumbnail statistic that 80% of data in companies is unstructured or semi-structured. Just to clarify the meanings of those terms, an unstructured data artifact would be a document, an email, a video or audio clip. A semi-structured data artifact would include data that does not conform to the norms of structured data but contains markers or tags that enforce some kind of loose (or not so loose) structure. XML documents would be an example of semi-structured data.  Tagged documents in a Knowledge Management system would also fit into this definition.

Structured data is what we would find in any database – a Data Model has been defined and the data is physically arranged within this model into tables. The data in these tables is described with metadata (i.e. data types (such as “character”) and the maximum length of that data (number of bytes)).

The methods of data creation are multiplying and the velocity of its creation are increasing. And that, in itself is a complicating factor. Some analysts (IDC, for example), predict that the Digital Universe -  that is, the world’s data – will increase by 50x by 2020. There will be in the same period, a growing shortage of storage, which will drive investment in the cloud as both individuals and corporations look for scalable, ubiquitously accessible, lower-cost and environmental data storage options. In addition, the same study predicts that of all that data, unstructured data, especially video, will account for 90% of that data.

There is also an important historical dimension to Big Data. For decades, companies have been hoarding structured, semi-structured and unstructured data in hopes of one day being able to extract value from it at some point in the future.

A large percentage of all this data will come with a wrapper of automatically generated Metadata – that is, (as indicated above), data about (or that describes) that data. A practical example could be the generation of a data artifact coming wrapped with metadata from those GPS enabled, media rich, socially linked mobile devices we all carry with us that transparently capture location, GPS coordinates, time, weather conditions and a plethora of other data elements when you click that holiday photo with your mobile phone. IDC predicts that such metadata is growing twice as fast as data.

It is clear from the last three paragraphs that Big Data describes explosive growth in data and metadata and an equally explosive opportunity to capture, tame and corral that data to extract value from it.

So the case has been made that we have a lot of data today and we will have even way more tomorrow, but should your organization be investing in Big Data today?

In a sense, probably you already are. Enterprise Business Intelligence environments lay a solid foundation for the next phase of Big Data. EBI is an earlier iteration of Big Data and, married to tools such as Hadoop and NoSQL databases for example, enable a natural evolutionary growth curve to your mastery of your information ecosystem.

Big Data has a requirement for a new way of thinking, new tools, clustered commodity hardware and probably, substantial investment. It comes down to your business, and if there is a clear value-based case to present that data to your company’s brainpower. The actual needs for this will be radically different depending on your industry. Oil and Gas may be interested in leveraging real time alerts in wellhead data or analyzing petabyte seismic datasets.  Packaged Goods multinationals may be interested in monitoring and engaging advocates, detractors and influencers across multiple Social Media platforms, mining and understanding sentiment and identifying problem areas in real time in order to identify opportunity or identify and avert potential brand-damaging events. Financial institutions may be interested in monitoring international money traffic to identify fraud or illegal activity. Government entities may mine extremist forums, or other unstructured data traffic to identify national threats.

Big Data can serve these needs in real time, enabling rapid (or even automated) response to flagged events. Whether it is a fit for your organization today would be determined through viewing your industry and business through a critical lens on your current Information Intelligence maturity, a strategic assessment of the data and information assets currently owned or available to your organization, and a prioritization of potential initiatives. How much data you harness and convert into information should be a key outcome required from this exercise. The opportunities are legion, but initiatives should have clear objectives and success metrics understood prior to a project kickoff.
Whether it is today or tomorrow, Big Data is becoming mainstream through necessity. Whether that is a road your organization wants, or needs to drive today, is something all medium and large organizations should be considering now.

What are your thoughts on Big Data? Is your organization currently considering Big Data as a strategic imitative or Proof of Concept?

Sliced or Shaved? Avoiding spreading your BI team too thin

 Post written by Chris S., BI Consultant at Ideaca. Read more about BI on his blog: The Outspoken Data Guy.

As a consultant with a background in Agile, I often get questions about how Agile can be used to solve certain problems that people are having with their Business Intelligence Programs.

I recently sat with a client to listen to some of the issues that they are currently having with their BI program. One of the biggest issues that this client is facing is what I would classify as a simple supply and demand problem. Basically their team of around 8 people cannot keep up with the demands of developing and sustaining their BI/DW environment in what is a large organization. The main question for me was could Agile help solve this problem. In my experience, Agile cannot solve the problem directly but it can be used to highlight the root cause.

This is a very common problem that BI programs face. It is the fact that teams are often small relative to the size of an organization and are also too small to manage the tasks that they need to perform to grow and maintain a BI portfolio. And in certain circumstances it is compounded by the fact that teams are often staffed with the wrong skills sets needed to grow and manage a BI offering.

So how can Agile help?

With proper tracking and monitoring of what the team does on a daily basis, teams can begin to gather data on what types of work the team is doing on a daily basis. What we often find is that at a certain point new development will stop coming from small teams charged with both the development and sustainment of a program as they cannot keep up with both. The ironic thing is that most BI managers have no real data to back this up. So taking advantage of some of the rigor around agile in terms of tracking what is done on a daily basis and how slowly new work burns down, one can begin to understand and report better on how time is spent and in fact how little time is available to delivering new functionality.