Everyone in business maintains some level of vigilence over their competitors. IBM watches HP closely, Deloitte watches PwC, Apple peers over their shoulder at Google. Although I agree in many cases, I often see companies blindsided by a "non-traditional" competitor which begs the question, who really is the competition? I'm not waxing poetic about inner-demons, the crazed lone employee who steals the company secret recipe, the equally crazy genius who takes his unorthodox and ridiculed ideas elsewhere, nor those competitors the analysts and investors have identified for the CEO. There is one very significant competitor few seem to realize ever, even after that competitor has disrupted their business. Perhaps there is an MBA term, but not having an MBA I'll coin my own for this entity: the Hidden Competitor.
Hidden Competitors are not obvious, primarily because they are not trying to hide. Innocently they execute on their business model day in and day out doing whatever it is they do. These companies are off the radar because they don't compete head to head with those companies they are disrupting. What they are doing is changing expectations: of customers, business partners, and possibly even the market. Although there are many examples one of my favorite goes back to a conversation at the Disney Company several years ago.
While providing consulting services at Disney World I asked a Disney executive what he thought about the recently opened Isles of Adventure at Universal Studios. He said he wasn't concerned. I asked him if he felt that way because of Disney's superior product, the head start Disney had on the Disney-MGM Studios, or perhaps the size of the tourism business in Orlando. No. He said he wasn't worried because Universal doesn't elevate a guest's expectations on service. What? He went on to explain he worries about those companies who provide their customers a great customer experience. Why? Those same customers come to Disney World as guests and expect Disney to provide an even better experience, the best in the world. Wow! Who was on his radar? Starbucks, WalMart, and FedEx. I was shocked. When I saw Disney's NexGen concept roll out there was no question in my mind, whether proactive or reactive, there was some company in their rearview mirror they saw coming on quickly preparing to disrupt their business.
Today disruption is a tremendous challenge. Our big industries and big companies do not react well to change that is unplanned. As a result retail, banking, communications, auto, insurance, and just about every other corner of the business world is under threat by Hidden Competitors. Although it doesn't take a wild imagination to see a future with the Mall of Amazon, Bank of WalMart, Google Networking (Kansas City ring a bell?), Apple Car, or PayPal Insurance; the real threat is in reacting quickly enough to the Hidden Competitor who disrupts your business from afar. Who redefines the expectations of your customers, partners, and even employees. Whomever reacts quickest to meet the changed expectations has the opportunity to gain market share, rapidly. Disruption does not happen over night, however it's rarely recognized when it hits the market. At first disruption is dismissed, then recognized for what it is, and finally panic sets in and everything but the kitchen sink hits the wall. Perhaps someday I'll understand why so many companies don't start planning for the disruption at the start. Sure, some ideas will fail. However what is the cost of preparation vs the cost of reaction?
Naturally this challenge aligns with the bigger issue of large companies innovating effectively; not a strong suit. Large companies are struggling to keep apace of the consumerization of technology and gaining a deeper understanding of social media. As they invest their time and effort, I hope they consider the actions of companies in other verticals beyond the cursory glance of what technologies they are using and how. Focus on understanding how they are changing the expectations of those they interact with on a daily basis. Consider how these new expectations will impact your business. And define a course of action to disrupt yourself in anticipation rather than waiting until after you've dismissed it, recognized it, and hit panic mode.
Thursday, February 21, 2013
Monday, February 11, 2013
The Next Evolution of IT
The times they are a changing...how trite! It's amazing how bad humans are at change considering nothing in our life is constant, including ourselves. However it's also true that some things never change. Frankly it is this dichotomy that generates the employment of millions in the field of consulting. One group of consultants tells companies how to change losing sight of the constants, another group advises on how to reduce the variables to regain consistency. Then there's this small group, of which I'd like to think I'm a member, who advise state change where a new set of constants and variables apply. So you can imagine in cloud computing with everyone running around helter-skelter just perhaps what's happening is a state change.
Operating models must evolve in reaction to evolving market forces. As a result processes, procedures, and tools change too and as there are a variety of approaches there are a variety of options. As the primary tool provider, IT must deliver new tools supporting the new business operating model. However to achieve its goals IT must evolve its own operating model.
In comparison to double entry accounting, invented in the early 15th century, IT is new, only decades old. Once the mainframe was invented the pace of business innovation has accelerated on a yearly basis. Every year we move further with digitizing business processes to drive productivity gains and establish new products and services. As a result the pace of business innovation is inextricably tied to that of technology; a company cannot win in one without winning in the other.
Focusing on just the past twenty years, advancements in technology have given rise to the Internet, email, chat, smartphones, blogs, micro-blogs, eCommerce, and tablets. IT has valiantly tried to stay ahead while falling further and further behind the curve. Against this backdrop IT budgets have been squeezed, talent hard to attract and keep, and risk tolerance all but eliminated. As a result IT has been forced into an ever escalating challenge to fund the future with reinvestments from the successes of previous investments. Finally, to this we now add the unknowns driven by the Consumerization of IT. Wow! It's a wonder IT hasn't imploded. By comparison in the world of business using an IT timeline, it's like moving from the single proprietor merchant of the 1700's to WalMart in 50yrs. But of course IT gets no credit for the size of the challenge. As viewed by the business results have been largely a disappointment with isolated wins punctuated by innovations which are driving real revenue. I measure disappointment by how rarely I hear anyone in business extol the virtues of their IT organization. Instead the perpetual complaint continues to be "too slow, too expensive" and the wins too few and far between.
After 50yrs of trying the same approach it's time to evolve. IT does not operate in a vacuum; the world is too big and too complex. Like everyone else, IT needs a list of friends to call when its time to move the couch or build the fence. It's time to recognize this need and formally adopt it as the central element of our IT strategy; the indoctrination of operating as an Ecosystem. In doing so we recognize we don't operate alone, we need to grow relationships and complimentary capabilities. Our focus shifts from building solutions to finding and adopting solutions. Its subtle, but this is what the business has been clamoring for over the past decade (or two). We move IT up the value chain from service or technology provider to solution provider, focusing on the solution to a business problem rather than its constituent technologies. Changing our approach will require a culture shift including a massive shift in skills. Today we manage information technologies with a design, build, run mindset. To meet the business goals today and in the future we need to focus on business solutions with an architect, oversee, audit approach. With this change, who provides the design, build, run skills go? The ecosystem. Who makes sure the right things are built the right way at the right time for the right value? IT in partnership with the business.
IT will never deliver on the ideal model: free, instantaneous, and clairvoyant. However that doesn't mean the business will ever release IT from these expectations. The Ecosystem approach shifts the operating model from developing technologies to providing a solution. Time to market opportunities in a highly competitive market necessitate a dynamic mix of capabilities. Its time for us to admit IT doesn't know everything, and it can't. Instead of trying to hire and train every conceivable technology expertise, and always falling short, IT needs to raise the bar and its game focusing on leading, not constructing.
Ecosystem based IT uses time to market and cost as primary drivers, along with requirements, to make quick decisions of rent, lease, buy, or build. Combine this with a strategic decision to jettison assets (see my earlier post on Assets are Evil) and you get the kind of agile, efficient and elastic IT leaders in the C suite are clamoring for and strategically minded CIO's are striving to deliver.
Operating models must evolve in reaction to evolving market forces. As a result processes, procedures, and tools change too and as there are a variety of approaches there are a variety of options. As the primary tool provider, IT must deliver new tools supporting the new business operating model. However to achieve its goals IT must evolve its own operating model.
In comparison to double entry accounting, invented in the early 15th century, IT is new, only decades old. Once the mainframe was invented the pace of business innovation has accelerated on a yearly basis. Every year we move further with digitizing business processes to drive productivity gains and establish new products and services. As a result the pace of business innovation is inextricably tied to that of technology; a company cannot win in one without winning in the other.
Focusing on just the past twenty years, advancements in technology have given rise to the Internet, email, chat, smartphones, blogs, micro-blogs, eCommerce, and tablets. IT has valiantly tried to stay ahead while falling further and further behind the curve. Against this backdrop IT budgets have been squeezed, talent hard to attract and keep, and risk tolerance all but eliminated. As a result IT has been forced into an ever escalating challenge to fund the future with reinvestments from the successes of previous investments. Finally, to this we now add the unknowns driven by the Consumerization of IT. Wow! It's a wonder IT hasn't imploded. By comparison in the world of business using an IT timeline, it's like moving from the single proprietor merchant of the 1700's to WalMart in 50yrs. But of course IT gets no credit for the size of the challenge. As viewed by the business results have been largely a disappointment with isolated wins punctuated by innovations which are driving real revenue. I measure disappointment by how rarely I hear anyone in business extol the virtues of their IT organization. Instead the perpetual complaint continues to be "too slow, too expensive" and the wins too few and far between.
After 50yrs of trying the same approach it's time to evolve. IT does not operate in a vacuum; the world is too big and too complex. Like everyone else, IT needs a list of friends to call when its time to move the couch or build the fence. It's time to recognize this need and formally adopt it as the central element of our IT strategy; the indoctrination of operating as an Ecosystem. In doing so we recognize we don't operate alone, we need to grow relationships and complimentary capabilities. Our focus shifts from building solutions to finding and adopting solutions. Its subtle, but this is what the business has been clamoring for over the past decade (or two). We move IT up the value chain from service or technology provider to solution provider, focusing on the solution to a business problem rather than its constituent technologies. Changing our approach will require a culture shift including a massive shift in skills. Today we manage information technologies with a design, build, run mindset. To meet the business goals today and in the future we need to focus on business solutions with an architect, oversee, audit approach. With this change, who provides the design, build, run skills go? The ecosystem. Who makes sure the right things are built the right way at the right time for the right value? IT in partnership with the business.
IT will never deliver on the ideal model: free, instantaneous, and clairvoyant. However that doesn't mean the business will ever release IT from these expectations. The Ecosystem approach shifts the operating model from developing technologies to providing a solution. Time to market opportunities in a highly competitive market necessitate a dynamic mix of capabilities. Its time for us to admit IT doesn't know everything, and it can't. Instead of trying to hire and train every conceivable technology expertise, and always falling short, IT needs to raise the bar and its game focusing on leading, not constructing.
Ecosystem based IT uses time to market and cost as primary drivers, along with requirements, to make quick decisions of rent, lease, buy, or build. Combine this with a strategic decision to jettison assets (see my earlier post on Assets are Evil) and you get the kind of agile, efficient and elastic IT leaders in the C suite are clamoring for and strategically minded CIO's are striving to deliver.
Thursday, February 7, 2013
The Data War and Mobilization of IT
In the end everything is about data. We use data to make decisions which, combined with thumbs, helps to separate we humans from primates. Today the supply of data far outstrips the demand for its use. We create data all day, every day, and everything we do creates data. From shipments to tweets, from logins to purchases, there is a "paper" trail behind every step we take. It's not too surprising that Cisco estimates a 13 fold increase in global internet data traffic on mobile devices from 2012 to 2017. That's an astounding number! Naturally such incredible growth will require wireless providers to expand their bandwidth, companies to expand their storage and compute to utilize the data, and new tools and techniques to make use of all that data. Last thing we want to do is just leave all that data laying around, collecting dust, right? True, but unfortunately that's the most likely scenario.
Although we are good at using data, we are only good at using familiar data. We are not so good at using data folded between complex relationships, the data equivalent of the fog of war. Why? In part I believe because we are creatures of habit who often use intuition rather than deduction to drive our decisions. However companies rightly view data as treasure, the new gold, capable of providing new insights which can in turn generate new business opportunities. Data is seen as objective, the "truth". This is the challenge of Big Data; to provide humans with the tools to overcome our innate inability to see trends and gain new insights through the fog of war.
Of course data can only provide value in decision making if the analysis is ready and relevant before the decision needs to be made. I call this Real Time Analytics which is the business solution enabled by the concept of Big Data. We have plenty of examples in life and business where companies have waited too long for the right answer when a good enough answer would have carried the day. Leaders at all levels need guidance from data analysis to make decisions. Whether in the form of an answer (this is what you should do) or simply insights (here is what is happening), we now realize a good decision today is better than a great decision tomorrow.
So our future is one of making better informed decisions faster using the ever expanding scope of data we generate combined with increasing capabilities to analyze it. Sounds great, but is IT structured to handle the work? Our IT departments have been designed with a centralized model; bring everything back to a subset of locations which house massive amounts of network bandwidth, compute, and storage. A 13 fold increase in mobile internet data traffic means more data, faster and a growing fog of war. The implications for companies moving Big Data programs mainstream is enormous. There is a point at which a centralized architecture simply will not work; it will not be possible to bring all the data back to one place to perform the calculations and then distribute the results again in the time frame required by Real Time Analytics.
In short, data does not scale vertically. We've already maximized its compression and transmit it at the speed of light. We are up against the physical laws of nature. There is no solution on the horizon enabling us to transmit data in ever increasing increments faster from one location to another. Instead today we have a linear relationship between the quantity of data being analyzed and the time it takes to analyze it. There is a model, popular in discussion but often misunderstood and misapplied in practice, which addresses the scalablity issue of data: parallelization. If we perform the calculations on a set of data in parallel rather than one at a time in serial, we can reduce the time required for analysis (note this approach is not always viable). Parallelization is built into ETL (Extract, Transform, Load) tools and is at the heart of Big Data tools such as Map Reduce (the foundation of Hadoop). Once data can be processed in parallel, processing can occur in a distributed/federated environment with reliable, repeatable results. Taken to its logical extreme if data were analyzed at its point of origin, some percentage of the overall analysis workload would be as distributed as possible. The net result is greater throughput of the overall system and thus reduced cycle times for analysis. It's like adding fog lights to the jeep traversing the fog of war focusing on the delivery of answers, not raw data.
We need prepare IT for a new world where the "work" is done as close to the user as possible, what I call mobilizing IT. Now that we understand parallelization and have been applying it in various forms for over a decade, it's time to unleash it's power by moving out of the traditional data center (several will note much of this trail has been blazed already by the Content Delivery Network). One of the first challenges we must be girding up to solve is how to push the analysis of data out toward the endpoints where the data is collected. It turns out the point of origin for much of the data being generated is very near storage and compute resources whether in the device (mobile phone) or one hop away on a network (cloud). Combine this with in-network data management and routing capabilities and the solution is very compelling. Of course there are ancillary benefits as well, such as the opportunity to architect a solution for continuous availability rather than the more expensive but less stable approach of disaster recovery. Real time compliance routines could be applied. The opportunities are endless, however the solutions are few.
Decomposition is a great approach to making big problems solvable. We have grown IT into a monstrous centralized monolith which boggles our minds. As our data sets explode we need to think about new approaches, and one approach worth considering is federating our data. We'll need an index mechanism with associated service to locate data so it can be used properly. We can leverage the index metadata to make real time decisions on how to execute the analytics. How much will be done at the endpoint, where will the data be collected and sub-analyzed, at what point can analysis stop because we have the "good enough" answer. We need to stay ahead of the data war fog.
Although we are good at using data, we are only good at using familiar data. We are not so good at using data folded between complex relationships, the data equivalent of the fog of war. Why? In part I believe because we are creatures of habit who often use intuition rather than deduction to drive our decisions. However companies rightly view data as treasure, the new gold, capable of providing new insights which can in turn generate new business opportunities. Data is seen as objective, the "truth". This is the challenge of Big Data; to provide humans with the tools to overcome our innate inability to see trends and gain new insights through the fog of war.
Of course data can only provide value in decision making if the analysis is ready and relevant before the decision needs to be made. I call this Real Time Analytics which is the business solution enabled by the concept of Big Data. We have plenty of examples in life and business where companies have waited too long for the right answer when a good enough answer would have carried the day. Leaders at all levels need guidance from data analysis to make decisions. Whether in the form of an answer (this is what you should do) or simply insights (here is what is happening), we now realize a good decision today is better than a great decision tomorrow.
So our future is one of making better informed decisions faster using the ever expanding scope of data we generate combined with increasing capabilities to analyze it. Sounds great, but is IT structured to handle the work? Our IT departments have been designed with a centralized model; bring everything back to a subset of locations which house massive amounts of network bandwidth, compute, and storage. A 13 fold increase in mobile internet data traffic means more data, faster and a growing fog of war. The implications for companies moving Big Data programs mainstream is enormous. There is a point at which a centralized architecture simply will not work; it will not be possible to bring all the data back to one place to perform the calculations and then distribute the results again in the time frame required by Real Time Analytics.
In short, data does not scale vertically. We've already maximized its compression and transmit it at the speed of light. We are up against the physical laws of nature. There is no solution on the horizon enabling us to transmit data in ever increasing increments faster from one location to another. Instead today we have a linear relationship between the quantity of data being analyzed and the time it takes to analyze it. There is a model, popular in discussion but often misunderstood and misapplied in practice, which addresses the scalablity issue of data: parallelization. If we perform the calculations on a set of data in parallel rather than one at a time in serial, we can reduce the time required for analysis (note this approach is not always viable). Parallelization is built into ETL (Extract, Transform, Load) tools and is at the heart of Big Data tools such as Map Reduce (the foundation of Hadoop). Once data can be processed in parallel, processing can occur in a distributed/federated environment with reliable, repeatable results. Taken to its logical extreme if data were analyzed at its point of origin, some percentage of the overall analysis workload would be as distributed as possible. The net result is greater throughput of the overall system and thus reduced cycle times for analysis. It's like adding fog lights to the jeep traversing the fog of war focusing on the delivery of answers, not raw data.
We need prepare IT for a new world where the "work" is done as close to the user as possible, what I call mobilizing IT. Now that we understand parallelization and have been applying it in various forms for over a decade, it's time to unleash it's power by moving out of the traditional data center (several will note much of this trail has been blazed already by the Content Delivery Network). One of the first challenges we must be girding up to solve is how to push the analysis of data out toward the endpoints where the data is collected. It turns out the point of origin for much of the data being generated is very near storage and compute resources whether in the device (mobile phone) or one hop away on a network (cloud). Combine this with in-network data management and routing capabilities and the solution is very compelling. Of course there are ancillary benefits as well, such as the opportunity to architect a solution for continuous availability rather than the more expensive but less stable approach of disaster recovery. Real time compliance routines could be applied. The opportunities are endless, however the solutions are few.
Decomposition is a great approach to making big problems solvable. We have grown IT into a monstrous centralized monolith which boggles our minds. As our data sets explode we need to think about new approaches, and one approach worth considering is federating our data. We'll need an index mechanism with associated service to locate data so it can be used properly. We can leverage the index metadata to make real time decisions on how to execute the analytics. How much will be done at the endpoint, where will the data be collected and sub-analyzed, at what point can analysis stop because we have the "good enough" answer. We need to stay ahead of the data war fog.
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