Updated: 7 min 44 sec ago
We – technology stakeholders, executives, consultancies and analysts – are wrong about enterprise IT.
Since the early days of the internet boom, enterprise IT has been criticized for not being responsive, transparent, flexible, and innovative. We believed that leadership, organization, workforce, culture, and vendors were the culprits. We were convinced that a fix had to do with elevating the CIO role, acquiring new skills, outsourcing tasks, aligning strategies, knowing customers better, and running IT like a service company. After so many years of religiously applying these recipes, enterprise IT is still facing the same criticism. Moreover, there is a growing trend of taking technology spending away from enterprise IT into the business and out to the third-parties with a hope of stimulating innovation, improving agility and reducing costs.
With bitcoin crossing the $4K mark and the market cap for cryptocurrencies currently residing around $140B, there’s a definite sense of a gold rush in progress much like the dot-com era and the real California gold rush of the 1800s.
While parallels with the dot-com era have been well reported, especially related to exploring what phase of the bubble we’re in, there’s been relatively less comparison with the California gold rush. So what can history teach us from the physical gold rush that may guide us in the midst of today’s digital equivalent? To help address this question, here’s some parallels between the two and some recommendations for organizations in terms of charting your course.
Back to school isn’t just about yellow buses, backpacks and pencils. For colleges as well as the cities and businesses that surround campuses, it means an influx of students and dollars. The fact that just about all of those people will be carrying mobile devices means there’s far more data available than ever before that can help local businesses get a better handle on who’s in town and uncover potential opportunities.
When my firm UberMedia evaluated Washington, D.C.’s Georgetown neighborhood, home to schools including Georgetown University and George Washington University, earlier this year, we used data showing the pathways to well-known shops there such as Anthropologie and Banana Republic. Anonymized mobile location data can tell us a lot – where people come from, how long they spend in each location and where they travel afterwards. Even in that simple form without additional data layered on, it’s powerful information for these large international retailers.
Historically, the race for an edge using big data was about piping in as many data feeds as humanly possible and getting access to that data as close to real-time as possible. A lot of time and investment has been spent solving API access and data latency problems.
As we dig one level deeper, however, it would appear we’ve focused entirely too much attention on the accumulation and storage of the sea of big data and not nearly enough time ensuring the full accessibility of that data.
According to Forrester, less than 0.5% of all data is ever analyzed and used. And yet, in a recent webinar hosted by InfoTrust, Richard Joyce, Senior Analyst at Forrester, said that “Just a 10% increase in data accessibility will result in more than $65 million additional net income for a typical Fortune 1000 company.”
As a former product manager, I was curious about whether the concept of A team versus B team existed within IT organizations as well. To facilitate this #CIOChat, I told participants about a person that I met at Apple several years ago. This person’s business card read “Newton Scapegoat”. I obviously asked, “why would someone take on such a title?” The person said that Apple’s A team was spun off as General Magic. For those that do not remember, General Magic developed many of the concepts of what mobility is about. According to the “Newton Scapegoat” when Scully did not get the power of mobility, he spun General Magic off. But soon after doing this, his opinion changed. He then scrounged around for B players and gave them a sadly impossible agenda—doing really hard things like hand writing recognition. As you either remember or can guess, the B team failed miserably with an impossible agenda.
Businesses are often criticized for not having strict policies for information security. However, this criticism is not inaccurate. Important information security practices are often overlooked despite all the major hacks discovered in recent years. It is unfortunate that preventive measures are often adopted only after a crippling incident.
It is not only the hacks that threaten businesses throughout the world. Self-propagating malware is perhaps an even greater threat. The release of Eternalblue and Doublepulsar exploits from the NSA hacking toolset led to the worldwide Wannacry malware attack that took down several businesses. With an online presence becoming a necessity for even small businesses, malware creators have even greater incentives to launch attacks. As a result, businesses need to look into tightening their security policies before it is too late. With that in mind, let’s examine some important policies that businesses need to take into consideration in this regard.
How well are your employees playing together? Are they playing in harmony or are they slightly out of tune?
I am an amateur musician (flute, piano and bassoon) and have performed with numerous orchestras and groups. Currently I am the principal bassoonist for the Broomfield Symphony Orchestra. The BSO has more than 60 regular members, most are amateurs like myself. Individuals who have a passion for music. A group that comes together once a week to rehearse and performs five concerts a year. We spend, on average seven weeks rehearsing for each concert. Not a lot of time to ensure 60 people are perfectly aligned through every piece of music.
According to a Logicalis Global CIO survey[i], the likelihood that CIOs are left out of the IT purchasing decision process has grown every year since 2013 with only 60% of CIOs controlling technology spending in 2016. This trend will most probably continue in the future. Even more troubling, over 60% organizations created at least one new mobile app in 2015 without any IT involvement[ii].
Decision making in the enterprise has changed, and it's becoming very complex. The bigger the IT project is, the lower the odds that the CIO is controlling the decision on his own and the higher the odds that the CIO may not be involved at all in the decision-making process[iii].
As I talk with executives from around the world, it’s clear that their companies’ data to-do lists are changing. A few years ago, businesses were focused on gathering information — from internal systems, customers, suppliers, etc. But now that those aggregation hurdles have (mostly) been cleared, attention is shifting. Today, business executives are most concerned with this: What’s the best way for us to extract value from the deluge of data we’re collecting every day?
The challenge is incredibly daunting. After all, analysts predict that more data will be created this year than was created in the last 5,000 years combined! But raw, unstructured information is essentially meaningless. In order to benefit from the sea of available data, you need to filter, sort and synthesize it. Then, you’ll need the expertise of data scientists who can search for insights and effectively communicate their findings with other decision makers.
Let’s be honest, it takes a lot to get me excited about traveling to Scottsdale, Arizona. And NEXTCON, put on by Nextiva, is definitely one of the few events where I’m willing to trade in some desperately needed time off, and put it towards continuing education.
I’m not alone. Many CIOs head to the desert every year to hear from the leading voices in merging cutting-edge technology with new customer-facing strategies to deliver an exceptional customer experience.
This year’s list of speakers is impressive – including Tomas Gorny, Neil Patel and Nate McMahon.Tomas Gorny: Converting technology into good business
I love Gorny’s story because it speaks to the American dream, in every sense of the word. He arrived in the United States at the age of 17. From Poland, he knew almost no English. But, true to the American spirit, he got to work. And he didn’t just start working, but decided to start creating.
IDG Contributor Network: Here’s why behavioral analytics is the next generation of business intelligence
Businesses collect intelligence – immense quantities of it. This statistical information has the potential to help companies gain a market edge, streamline operations and improve profitability. The challenge exists in finding ways to collect a diverse set of data, and then compile it into a format that is actionable.
Design theory is one way that companies can better design their reporting dashboards so that everyone, not just those with a PhD, can benefit.
But it’s also important to attack the other side of the equation. Customer data is acquired through various channels: in-store traffic, mobile apps, website cookies, and social platforms, just to name a few.
IDG Contributor Network: Get your priorities straight before you start applying artificial intelligence in your business solutions
Artificial Intelligence (AI) has the potential to put you ahead of your peers in the industry. However, like with many opportunities, you have got to be keen at doing the right things in the right order.
On the adoption curve, AI is clearly in the "innovators" stage. The "movers and shakers" at Google, Baidu, Facebook, Nvidea, Qualcomm and other world-class AI organizations are definitely pushing things along but have major strides to make.
The pace seems to have slowed down recently, because they have run into limitations, for example the availability of high-volume, high-quality data. AI solutions require vast amounts of good data to be meaningful. The collection and formatting of data is challenging.
As companies move from merely enabling Internet technologies to deeper, more comprehensive digital transformations, it looked for a while like the point person in such efforts was going to be a new C-level title: the chief digital officer.
CDOs were charged with leading a company’s business from analog to digital, bringing in general management skills as well as deep knowledge about digital technologies. They were hailed as “transformers in chief” and CEOs-in-waiting. But according to PwC’s most recent Digital IQ survey, only 7% of organizations have a leader with the CDO title. (Disclosure: I am a principal at PwC.)
As economic and competitive pressures push organizations toward more rapid product and service delivery, the ways organizations engage with technology – and the people who support it – are changing. According to a recent report by CompTIA, Considering the New IT Buyer, 46 percent of U.S. workforce professionals say that who pays for new technology depends on the tool in question, signalling greater autonomy by line of business (LOB) managers to equip their teams with the right solutions.
With business units hiring their own IT professionals and managing technology independently, organizations should brace for the nuances of navigating decentralized IT resources, compared to traditional IT departments.
CIOs today face a unique HR-related challenge: Not only to recruit and retain the best possible talent, but also to deal with the technological expectations of an entire organization’s employees, when some of those employees were born in an era before color televisions, while others have grown up with smartphones and laptops as staples of daily life.
The modern workforce is comprised of five generations, from near-retirement Traditionalists born in the 1940s to the young adults of Generation Z just now entering the professional world. In the decades constituting this wide age gap, the accessibility of digital technologies has increased exponentially, as has the digital experience of end users. The younger generations, especially, expect technology and applications at work to be as fast, agile, and flexible as those at home. When users do not feel their needs are being fulfilled by IT departments that are either too slow to innovate or simply limited by multi-year investment cycles that make any implementation look dated, they find solutions outside the organization in third-party applications and platforms.
With most organizations now several years into their digital transformation journeys, many are looking to measure progress, gauge maturity, and benchmark against peers in their industry. The key questions are how to assess this maturity, what are the key pillars and elements of maturity, and which capabilities are new and different compared to business as usual.
Digital transformation is a broad subject that requires competency across strategy and vision, people and culture, process and governance, and technology and capabilities, as show in following chart:Nicholas D. Evans
Key pillars of digital transformation (Source: "Mastering Digital Business", BCS, 2017)
It’s hard to imagine any business that doesn’t use any form of technology these days. The problem is, any computing infrastructure or equipment can be exposed to various methods of cyberattacks. Just last May, the WannaCry ransomware affected more than 10,000 organizations of all sizes in more than 150 countries. The attack caused stoppages in critical services and operations such as the UK’s National Health Service and several of Renault’s automotive manufacturing plants. Last year, one billion Yahoo users saw their accounts hacked, costing the company dearly.
Many companies do business in the EU without having a physical business presence there. These companies have been able to collect, process, and protect their customers’ personal information with little regard for the various EU privacy laws. As of May 2018, this changes with the enforcement of the General Data Protection Regulation (GDPR).What is GDPR?
Since 1995 the EU has had a directive in place requiring member states to enact laws to protect personal information. The directive provides a framework for these laws. As you can imagine with 28 sovereign states, there are variations in how the laws have been enacted and how they are enforced. Additionally, businesses may need to interact with government officials, called data protection authorities or supervisory authorities, in each member state to legally perform the processing of personal information to run their operations.
Having wrinkles in a USB stick is certainly not great. But here’s some good news: Dry cleaners are taking care of it and remove them from your clothes before processing your laundry. To strike a more serious note, a study conducted by internet security firm ESET in the United Kingdom has revealed that 22,266 USB sticks and 973 cell phones are among the various gold nuggets found by dry cleaners in dirty laundry each year. However, a staggering 45 percent of the devices never make it back to their owners.
These numbers are alarming but only the tip of the iceberg. The phenomenon as such is a common and global issue, far beyond the borders of the UK – and beyond dry cleaning. These gadgets are fun to have, cheap, incredibly convenient, small in size, highly mobile by nature, and enormously capable in terms of their memory capacity. Yet the common assumption that most of these devices are protected these days is a misbelief. While some of them might end up in the garbage can, others are creating headlines in the press, causing public embarrassments and all too often severe financial and reputation damages.
While the development of the internet of things has revolutionized heavy industry, online shopping, localized data collection and virtually every other aspect of modern life and business, innovators are still struggling over the future of the IoT, and how they’ll get there. While many see big data as the driving engine behind the IoT, savvy investors and entrepreneurs have shown that the real power behind the interconnectivity phenomenon is artificial intelligence.
Tapping into the potential of AI won’t be easy for innovators, but doing so will be far more profitable for the IoT’s future than relying on big data alone. As programmed intelligence grows to new and greater heights, its ability to optimize the IoT will only be enhanced.