The Dark Side of Digital

 Four years ago, I wrote reflecting on my 50 years in IT, and the pursuit of value from the use of IT. I described the changes that had occurred over that time since I started my working life as a computer operator on an IBM 1401, which had a (not really published as such) processing speed close to 10 million times slower than today’s (2013) microprocessors, 8k of storage (later upgraded, with an additional unit, to 16k), no solid state/hard drive, displays or communication capability, and no operating system (that was me!). Weighing in at around 4 tons, it needed a fully air conditioned room, with a raised floor, approximately twice the size of my living room.

I described how my world in 2013 compared with that time. I had powerful technology in my small home office, wirelessly connected within my house, and to the world beyond through the internet. I had access to an ever-growing body of knowledge that could answer almost any question I had, and which enabled me to manage my banking, pay bills, check medical lab test results, organize travel, shop, read books, listen to music, watch videos, play games, organize, edit and enhance photographs and videos, and a myriad of other tasks.

I went on to describe how, beyond my individual world, at the enterprise level, the technology model is changing from computing – the technology in and of itself, to consumption – how individuals and organizations use technology in ways that can create value for them and, in the case of organizations, their stakeholders. I discussed the extent to which technology, and how it was being used, was continuing to change, at an ever-increasing rate, including:

  • increasing adoption of the Cloud;
  • Software (and just about anything else) as a Service; the explosion of “Big Data”, and, along with it, analytics and data visualization;
  • mobility, consumerization and BYOD which fundamentally changes how, where and when we interact with technology and access information;
  • the ”internet of things” (IOT) bringing with it unprecedented challenges in security, data privacy, safety, governance and trust; and
  • robotics and algorithmic computing which have considerable potential to change the nature of work.

I closed by talking about what hadn’t changed, and what needed to change. Putting my value lens on, I lamented that, then, 15 years since The Information Paradox, in which I described the challenge of getting value from so called “IT projects”, was first published, the track record remained dismal, and realizing the value promised by IT remained elusive. I attributed this situation to several factors, the primary ones being:

  • a continued, often blind focus on the technology itself, rather than the change – increasingly significant and complex change – that technology both shapes and enables;
  • the unwillingness of business leaders to get engaged in, and take ownership of this change – electing to abdicate their accountability to the IT function; and
  • failure to inclusively and continually involve the stakeholders affected by the change, without whose understanding and “buy in” failure is pretty much a foregone

 

What a difference four years makes

OK – that’s (probably more than) enough of a recap – I’m now going to fast forward some 4 years (a lifetime in the digital world) to today, 2017. While the challenge of creating and sustaining value from our use of technology described above is still real, our failure to address it, along with an almost total failure of leadership – technical, business and government leadership, have brought us into an increasingly dark place – one that I think few of us saw coming, certainly not unfolding as it is. I call this place “the Dark Side of Digital”. I alluded to it in 2013 in discussing IOT, robotics and algorithmic computing, when I said that they brought with them “unprecedented challenges in security, data privacy, safety, governance and trust…(and) have considerable potential to change the nature of work” – I would now revise and add to the latter saying “…have considerable potential to fundamentally impact the future of work and, indeed, the future of society”.

The elements of this dark side fall into three main categories:

  1. Cybersecurity: This is the most traditional category – one that, albeit not so- named, has been with us since the advent of computers, when cards, tapes or
    other media could be lost/stolen. However, as our connectedness continues to increase, so does our susceptibility to cybersecurity attacks, with a growing number of such threats arising out of machine-to-machine learning and the Internet of Things. There are nearly 7 billion connected devices being used this year, but this is expected to jump to a whopping 20 billion over the next four years. Most cybercriminals are now operating with increasing levels of skill and professionalism. As a result, the adverse effects of cyber-breaches, -hacks, or –attacks, including the use of ransomware and phishing continue to escalate resulting in increased physical loss and theft of media, eroding competitive advantage and shareholder value, and severely damaging reputations. More severe attacks have the capacity to disrupt regular business operations and governmental functions severely. Such incidents may result in the temporary outage of critical services and the compromise of sensitive data. In the case of nation-state supported actors, their attacks have the potential to cause complete paralysis and/or destruction of critical systems and infrastructure. Such attacks have the capacity to result in significant destruction of property and/or loss of life. Under such circumstances, regular business operations and/or government functions cease and data confidentiality, integrity, and availability are completely compromised for extended
  1. The Future of Work: The fear that technology will eliminate jobs has been with us pretty much since the advent of the first commercial computers, but, until the last few years, the argument that new jobs will appear to replace the old has largely held true. Now however, the revolutionary pace and breadth of technological change is such that we are experiencing a situation in which, as recently described by the Governor of the Bank of England, Mark Carney.

“Alongside great benefits, every technological revolution mercilessly destroys jobs & livelihoods well before new ones emerge.”

Early AI and IOT systems are already augmenting human work and changing management structures across labor sectors. We are already seeing, and can expect to continue to see uneven distribution of the of AI impact across sectors, job types, wage levels, skills and education. It’s very hard to predict which jobs will be most affected by AI-driven automation.

While, traditionally, low-skill jobs have been at the greatest risk of replacement from automation, as Stephen Hawking says, the “rise of artificial intelligence is likely to extend job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining.” He goes on to say that “we are at the most dangerous moment in the development of humanity”.

  1. The Future of Society: On the societal front, a paradigm shift is underway in how we work and communicate, as well as how we express, inform and
    entertain ourselves. Equally, governments and institutions are being reshaped, as are systems of education, healthcare and transportation, among many others.

AI and automated decision making systems are often deployed as a background process, unknown and unseen by those they impact. Even when they are seen, they may provide assessments and guide decisions without being fully understood or evaluated. Visible or not, as AI systems proliferate through social domains, there are few established means to validate AI systems’ fairness, and to contest and rectify wrong or harmful decisions or impacts. Professional codes of ethics, where they exist, don’t currently reflect the social and economic complexities of deploying AI systems within critical social domains like healthcare, law enforcement, criminal justice, and labor. Similarly, technical curricula at major universities, while recently emphasizing ethics, rarely integrate these principles into their core training at a practical level[1]. As Mike Ananny and Taylor Owen said in a recent Globe and Mail article[2], there is “a troubling disconnect between the rapid development of AI technologies and the static nature of our governance institutions. It is difficult to imagine how governments will regulate the social implications of an AI that adapts in real time, based on flows of data that technologists don’t foresee or understand. It is equally challenging for governments to design safeguards that anticipate human-machine action, and that can trace consequences across multiple systems, data-sets, and institutions.” This disconnect is further adding to the erosion of trust in our institutions that we have been seeing over several decades.

Adding to the threats to society is the proliferation of internet and social media. In a world where we can all be publishers, we see shades of Orwell’s 1984 in a post-truth word of alternate facts, and fake news. Rather than becoming a more open and collaborative society, we see society fracturing into siloed echo- chambers of alternate-reality, built on confirmation bias, and fed by self-serving populist leaders, posing dangerously simplistic solutions – sometimes in tweets of 140 characters or less – to poorly understood and increasingly complex issues.

 

So, what do we need to do?

The complexity of these challenges, and their interconnectedness across sectors make it a critical responsibility of all stakeholders of global society – governments, business, academia, and civil society – to work together to better understand the emerging trends.

If business leaders expect to harness the latest technology advances to the benefit of their customers, business and society at large, there are two primary challenges they need to address now.

  1. As companies amass vast amounts of personal data used to develop products and services, they must own the responsibility for the ethical use and security of that information. Ethical and security guidelines for how data is collected, controlled and ultimately used are of paramount concern to customers, and rightfully so. To gain the trust of customers, companies must be transparent and prove they employ strong ethical guidelines and security standards.
  1. It is incumbent on organizations to act responsibly toward their employees and make it possible for them to succeed in the rapidly changing work environment. That means clearly defining the company vision and strategies, enabling shifting roles through specialized training, and redefining processes to empower people to innovate and implement new ways of doing business to successfully navigate this new and ever-changing

As a society, if we are to avoid sleepwalking into a dystopian future, as described in 2013 by internet pioneer Nico Mele as one “inconsistent with the hard-won democratic values on which our modern society is based… a chaotic, uncontrollable, and potentially even catastrophic future”, we must recognize that technology is not destiny – institutions and policies are critical. Policy plays a large role in shaping the direction and effects of technological change. “Given appropriate attention and the right policy and institutional responses, advanced automation can be compatible with productivity, high levels of employment, and more broadly shared prosperity.”

The challenge is eloquently described by WEF founder and executive chairman, Dr. Klaus Schwab.

“Shaping the fourth industrial revolution to ensure that it is empowering and human- centred, rather than divisive and dehumanizing, is not a task for any single stakeholder or sector or for any one region, industry or culture. The fundamental and global nature of this revolution means it will affect and be influenced by all countries, economies, sectors and people. It is, therefore, critical that we invest attention and energy in multi- stakeholder cooperation across academic, social, political, national and industry boundaries. These interactions and collaborations are needed to create positive, common and hope- filled narratives, enabling individuals and groups from all parts of the world to participate in, and benefit from, the ongoing transformations.”

 

A call to action!

We need, as Dr. Schwab goes on to say, to “…take dramatic technological change as an invitation to reflect about who we are and how we see the world. The more we think about how to harness the technology revolution, the more we will examine ourselves and the underlying social models that these technologies embody and enable, and the more we will have an opportunity to shape the revolution in a manner that improves the state of the world.”[3]

We cannot wait for “them” to do this – as individuals, we can and must all play a leadership role as advocates in our organizations and communities to increase the awareness and understanding of the changes ahead, and to shape those changes such that, as Dr. Schwab says, they are empowering and human-centred, rather than divisive and dehumanizing.

[1] Source: The AI Now Report, The Social and Economic Implications of Artificial Intelligence Technologies in the Near-Term, A summary of the AI Now public symposium, hosted by the White House and New York University’s Information Law Institute, July 7th, 20

[2] Ethics and governance are getting lost in the AI frenzy, The Globe and Mail, March 20, 2017

[3] Source: The Fourth Industrial Revolution: Risks and Benefits, Wall Street Journal, Feb 24, 2017

Getting Information Management Right

A couple of recent articles by Thomas Wailgum in CIO.com got me thinking – yet again – about information management (IM – for more on IM see Enterprise IT or Enterprise IM?). The first, Information Wants to Be Free, But at What Cost?, makes the point that the more information that enterprises continue to exponentially collect, the more difficult and expensive it’s going to be for them to understand and disseminate that information. The second, The Future of ERP, Part II, makes the case for change in that after four decades, billions of dollars and many huge failures, big ERP has become the software that no business can live without—and the software that still causes the most angst.

In The Information Paradox, and every time I present or discuss the topic of getting real value from our increasingly significant and complex investments in IT-enabled change, I use the slide below to explain how the way we use IT has evolved.

Slide1

When I started in this business, back in the early 60s, most, if not all commercial applications of IT were automation of existing tasks – where the focus was on doing the same thing more efficiently. I call this the appliance era – applications were stand-alone and very little business change was required (as illustrated by the pie chart on the slide). You could essentially have be given the application for Christmas – plug it in and it would do the job.

In the next era, which emerged during the 70s, things became  more complex. We moved beyond automation of tasks to creating, storing, distributing and manipulating information. The focus here was on effectiveness – using information to do things differently and to do different things. You now had to worry about what information was needed, by whom, where, when and in what form – and people had to be trained and incentivized to work differently. Appliances now had to work together in an integrated way, and the way business was done had to change – I call this the rewiring era.

In the next era, which emerged during the 80s, we began to see what I heard a Northrop Grumman CIO describe as “game changing plays” – changing the rules of existing industries and creating new ones. I call this the transformation era. While the changes might not be possible without the technology, the bulk of the effort required to achieve the desired outcomes involves changes to the business – including the nature of the business, the business model, business processes, peoples roles and skills, organizational structure, physical facilities and enabling technology. Those appliances – now ranging from “mainframes” to smart-phones – have  to work together in an integrated way, not only within an enterprise, but outside it – on a global basis.

Unfortunately, while our use of IT has evolved – our management of it has lagged. In far too many cases, the focus is still on the IT appliance  – “plug it in and the value will flow”. Those days are long gone. We are not today simply dealing with appliances – or with simple appliances – we are dealing with massive organizational and cultural change – transformational change. Change that is enabled by technology, but of which technology is only a small part.

The more that I have though about this, and talked about it, the more I feel that one of the sources of the perceived and real failure of investments in IT-enabled change to deliver the expected business value is that we have still not got the information piece right. (Note that in the following comments, I may appear to, and indeed do, to a certain extent, use the terms data, information and knowledge somewhat loosely. This is not because I do not understand the difference – or at least have an opinion on it – but because terminology in common use doesn’t always make a clear distinction, and I don’t want to bog this post down with that discussion.)

While the amount of data we store continues to grow – Gartner predicts that the amount of enterprise data will grow 650 percent during the next five years, a recent Forbes Insights survey of more than 200 executives and decision makers at top global enterprises found that nearly one-quarter of the respondents cited the availability of timely data as one of the top barriers to aligning strategy and operations today. In an earlier post, The Knowing-Doing Gap,  I quoted James Surowiecki, from his book, The Wisdom of Crowds, where he said “…information flows – up, down and across organisations – are poor, non-existent or “filtered” in all directions, decisions are made by a very few with inadequate knowledge and information, and there is limited buy-in to whatever decisions are made.” So, with an enormous and growing amount of data being collected, at considerable cost, why haven’t we got it right? I would suggest that there are a number of reasons for the current state of affairs:

  1. Knowledge is power
  2. Not knowing what information is relevant
  3. Too much information
  4. Bad data
  5. System complexity
  6. Go with the gut

Let’s examine each of these.

Knowledge is power

Building on the Surowiecki quote referenced above, Sir Francis Bacon was (among) the first to say that “Knowledge is power”. Peter Drucker expanded on this saying “Today knowledge has power. It controls access to opportunity and advancement.” This presents a cultural and behavioural barrier to sharing information and to getting it to (all) the people who need it – one that should not be under-estimated.

Not knowing what information is relevant

In another life, I led a lot of what we then called Information Resource Planning assignments. We would interview key stakeholders in an enterprise to find out what information they required. Once we had their requirements, I always asked one final question: “If you had this information, what would you do differently?” Very few people could answer this question or had even thought about it. Enterprises need to take an outcome and role based approach to identifying and meeting information requirements. Expanding on my earlier question, we need to ask: ” Based on the outcome(s) we want to achieve, what decisions/actions need to be taken, who needs to take them, and what information do they need – where, when and in what format – to take them, and what information do we need to know that things are working as they should be?”

Too much information

Today we are drowning in information and, as per the Gartner prediction above, it is only going to get worse. Even if the information that we require is available, it may be lost in the sheer volume of information – the information noise. This noise level is only going to increase. If we are to cut through this noise to what is relevant, it is even more critical to take an outcome and roles based approach to defining information requirements. We will also need to beyond the traditional reporting metaphor and simple, or simplistic dashboards to much more sophisticated, yet intuitive (see “System complexity” below) analytical and data visualization tools.

Bad data

One of the biggest risks to organizations is “bad data quality.” Results from Scott Ambler‘s September 2006 Data Quality Survey show that 46% of data have some data sources that are a “complete mess” or the data itself has serious problems. In an April 2009 data quality PRO survey of Data Quality in Business Intelligence, 42% of respondents reported minor issues, 50% reported major issues, and 4% didn’t know –  leaving just 1% reporting no problems. A 2007 Accenture CIO survey claimed that the costs of compromised data quality are clear—billions of dollars squandered each year due to mistakes, manual processes and lost business. Of the CIOs surveyed,  29 percent said that they had minimal or limited data quality efforts in place, even for critical systems, and only 15 percent of respondents believed that data quality was comprehensively (or near comprehensively) managed. Indeed, not a single North America-based organization reported that they have a fully comprehensive data quality program today. Information is only as good on the data it is based on. It will take time to implement workarounds for, and fix the mess that we have created. In the interim,  we need, at a minimum,  to know how credible the information is and what confidence we can have in decisions based on that information.

System complexity

ERPs were promoted as one “solution” to the information management challenge, but have  proven a challenge for many enterprises – see ERPs – Can’t live with them – Can’t live without them!. Where they have been successful, they may have done a good job of integrating data across enterprises, but few would describe them as easy to use. Even if relevant information is available, if it is too complex or time-consuming to get at it, people won’t. While somewhat simplistic, I have often felt, and even more often heard that “if I need to be taught how to use it, I won’t use it.” Again, information needs to be relevant, outcome and role based, and easy to access and understand.

Go with the gut

Business intelligence was identified in the 2009 SIM Trends Survey as one of the top technologies that enterprises were planning to invest in. Research reported by Accenture in 2008 found that close to half (40%) of major corporate decisions are based on “gut feel”.  The reasons for this executives cited most often, which reinforce some of the points above, were: because good data is not available (61 percent); there is no past data for the decisions and innovation they are addressing (61 percent); and their decisions rely on qualitative and subjective factors (55 percent). 23 percent of respondents identified “insufficient quantitative skills in employees” as a main challenge to their company, and 36 percent said their company “faces a shortage of analytical talent.” 39 percent of respondents said that IT capabilities restrictions were a major challenge and 27 percent said there was an inability to share information across organizations within their company. I also wonder if this might not also be a bit of the “cult of leadership” where they believe that they have achieved a level of knowledge/wisdom where they don’t need information to make good decisions.

Information and people are the two most important and, in all too many cases, the most ineffectively utilized assets in today’s enterprises. What information is available to people – be they executives, managers, workers, suppliers, customers or other stakeholders –  the quality of that information, and how they use it is a key part of what determines business success or failure – value creation and sustainment, or value erosion and destruction. This is true both for “business as usual” activities and – even more so – for transformational change. If enterprises do not get the information piece right, their transformational efforts, and their survival, will be in extreme peril.