Author: clarenceomoore

Good AI vs. Bad AI: The Myths, Hopes And Realities of the Machines

AI is about to reshape the enterprise workplace in a big and fundamental way, and any organization that hasn’t already started thinking about, planning for and adopting the new wave of smart AI tools is at risk of being left behind by their competitors.

Even at this early stage, it’s clear the benefits of AI in the office are going to be enormous, as these new tools work alongside employees — becoming a personal digital “coworker” — and augment our productivity and creative-thinking skills while freeing us from the monotony of the routine tasks that currently consume our workdays.

But it’s also clear that not all workplace AI is created equal — some of these new AI tools will be seamlessly adopted into your employees’ daily tech stack and workflows, like Slack, while others won’t be a good fit, getting the cold shoulder and ending up unused and unloved despite the best efforts of management and IT.

In other words, there is good workplace AI and bad workplace AI. The challenge enterprise leadership is now facing is figuring out how to tell the two apart.

Signs of bad workplace AI

Bad workplace AI creates more problems than it solves, holding back adoption rates and wasting everyone’s time. Look out for these warning signs.

Bad workplace AI requires significant customization to interact with and understand your office’s digital data. If the AI tool doesn’t work out of the box with the APIs of Office 365, Outlook and Google Mail, OneDrive and Dropbox, and the other standard platforms and apps of our workdays, your implementation cost and employee adoption rates will suffer.

Another example of bad workplace AI is AI that is not easily accessible by employees, who will be interacting with chatbots and AI assistants through a chat interface. If the AI tool doesn’t use an existing platform like MS Teams, Slack, or Skype, odds are employees won’t bother with the learning curve to use it, no matter how many training seminars you put them through. It’s in an enterprise’s best interest to create the most frictionless interaction possible when bringing in a new type of tech like AI to the workplace.

And finally, the biggest warning sign is AI not built from the ground up to solve the real-world problems your employees are facing. For example, one of the biggest challenges our offices are facing is the huge amount of time lost spent on menial, no-value tasks like booking meetings, searching for files and creating standard documents. These problems are solvable, and more importantly will deliver the easy and measurable wins you should expect from a new AI tool.

Welcoming good workplace AI

Don’t let these potential AI downsides scare you off workplace AI, because the potential of good AI can’t be underestimated. AI’s underlying technology has developed rapidly, and as a result AI has gotten a lot smarter in a really short amount of time, and can generate real value for the modern enterprise.

You can read a lot about AI tech like natural language processing and machine learning, but the key takeaway is this: AI-powered tools can now navigate and understand our workplaces’ digital information at the deepest level, automating tasks and unlocking new insights for employees while helping deliver major strategic gains for your organization.

It’s this advancement that is reshaping our workplaces and nature of work, from the cubicle to the corner office, as we gain the time, ability and mental energy to focus more on work that matters, while the menial tasks are offloaded to workplace AI assistants and similar tools, who we simply tell what we need done and get instant results.

For employees, this will unlock the literal hours spent each day on meaningless processes like coordinating and scheduling meetings and looking for documents across the cloud, apps and platforms are freed up. This time and energy can then be spent on high-value tasks. Even decision-making will be improved, as AI tools plug into and understand work data like sales figures, web analytics, and other metrics, making them accessible for all and generating new insights.

At the organizational level, these AI tools will help you hit strategic goals by quickly and easily expanding productivity, and even unlocking new sources of growth. While productivity is the easy win, it’s the additional value generated by employees being more engaged with the work they enjoy doing, putting more time and energy into challenging, creative work, that can result in major gains, like surfacing more ideas and innovation. It’s these gains that will help separate high-performing 21st century enterprises from their last-century peers.

by Roy Pereira, CEO of Zoom.Ai


Which matters most – vision, skill, effort, money or technology acumen?

Human endeavour is a powerful thing. It saw Amelia Earhart fly single-handedly across the Atlantic, Neil Armstrong on the moon and no end of people tracing the steps of others up the slopes of Everest, in the knowledge that they might not come back.

Many of our enterprises were originally formed on the basis of similar, beyond the call of duty effort — “One percent Inspiration, 99 percent perspiration,” as Thomas Edison was purported to say. The combination of money, vision, acumen and consistent, focused effort, even when all seems pointless — Sir Ranulph Fiennes calls this ’motivation’ — is only occasionally rewarded by remarkable success: the legions of failure go silently to their doom, like all those films we will never see because the hero gets killed in the opening scene.

It is against this background that we should view today’s technology superheroes — like Jobs and Gates before them, and many more before that (shout out to unsung hero Tommy Flowers, who had the drive and chops, but not the PR – hat-tip Jon Pyke), the current raft of Brin, Bezos, Zuckerberg and of course Musk, have had to deliver all of the above, over a period of decades.

Elon Musk has been close to failure more times than he dares think about, but the announcements keep on coming. For example, Tesla’s latest smart power grid experiment in Nova Scotia in collaboration with the Canadian Government, or DHL’s suggestion that the ROI of Tesla trucks may be better than expected, when maintenance costs are taken into account as well as fuel.

Meanwhile Amazon has moved from being a shaky stock to ‘corporate America’s nightmare’, according to Bloomberg. Jeff Bezos’ entire strategy, we are told, hinges on it being always ‘Day One’, plus a sharing model literally designed on a napkin. Yet the company holds entire industries in thrall, as do Google, Apple, Alibaba and the rest. So, to the elephant in the boardroom: why don’t other companies simply follow suit?

The answer is not about being the most technologically advanced: I’ve been told that Tesla’s battery technology is not the best on the market right now, and Amazon’s infamous recommendations algorithm was initially no better than any number of university machine learning projects. Don’t get me wrong, hardware and software engineering deliver great things — but their presence or absence is not the main lever.

Nor is the answer about money — you just have to look at the investments by technology giants to see that (a) they have plenty of it, and (b) they are spending just as much (if not more) than the upstarts. The very existence of FinTech is illustration that money can’t buy you innovation-led success.

Nor even is the answer about vision. Sorry. We can all come up with sweeping statements about how we are changing the world, but saying them doesn’t make them true, or effective. Last year Facebook changed its mission statement from “Making the world more open and connected” to “Give people the power to build community and bring the world closer together.” As well as copping out from any blame, the change reflects how Facebook enables change more than causing it: the rest is up to us.

So, is the answer down to ‘digital transformation’ or whatever the latest business change mantra might be? Again, the answer is no, as it puts the cart before the horse. Sadly, you will not be able to use technology to change the way you think, however much potential it offers. Analytics, cloud or whatever will not cause some kind of corporate epiphany at the top, nor anywhere in the hierarchy.

No, no, no and four times no. Rather, the answer is down to doggedness within a context fraught with uncertainty, ignoring anyone that might tell you that you are an idiot (because, frankly, you probably are). Today’s companies are shackled by stock market valuations, quick-buck investors and risk-averse management. It is completely unsurprising that Amazon went from being a loss maker to one of the world’s most valuable stocks — like all of the best stories, it snatched victory from the jaws of defeat. As the Bloomberg author Shira Ovide remarks, “This was a case of preparation meeting opportunity.”

So, is it the case that traditional industries should follow suit, taking huge gambles and risking shareholder wrath? No, as this isn’t an either/or game. Despite the repeated public failures of the Musks and Bezoses, Zuckerbergs and Jobsian inheritors, behind the scenes are well-oiled machines that see experimentation as part of business as usual. Even if the hero does get killed, that’s OK, because these people have more than one story to tell.

Don’t get me wrong, many organisations are making great strides (check out what Philips is becoming, for example). But many more that I have worked with are looking to become better at this innovation thing, without actually addressing the most significant factor — a need to put “doing new things” in front of “doing old things”. That’s in front, not alongside or somewhere over there. My experience working internally in some of our biggest institutions is that they simply don’t have the determination to do it.

As long as this is true, no amount of lean or agile, DevOps or predictive decisions, transformation, digital-first strategy or anything else we can come up with, will make any difference. Sure, individual departments may have something to feel proud about, a new app or service, a new type of account, operational approach or customer portal.  But as long as these are the exception, not the norm, they will not make much of a difference in the longer term.

Corporations have few guarantees in this tumultuous age, but one thing is for sure. While success is not pre-ordained, any company without a positive attitude to change is on its own death march. Perhaps, for the executives currently in place, this doesn’t matter — they will just move on and take their salaries with them. However, if they do not accept the need to embrace change as normal, and shoulder the burden of consequences with grit and determination, they will be failing all of their stakeholders, customers, investors and employees alike.


Image by Wang Lama Humla, with thanks.

Follow @jonno on Twitter.

3 Tech Areas in Which Engineers Are Having a Big Impact

We all know that technology has changed the world dramatically in recent years, and continues to disrupt industries of all types, in all locations across the globe. For engineers, and for businesses which employ them and/or use their developments, the meshing of engineering and technology is particularly powerful right now. By pairing humans with computers, some of the most exciting projects going around are currently being released, or are under development.

Whether you’re interested in control systems engineering, biomedical engineering, computer engineering, or another specialty, it’s important to stay up to date on the latest developments. Read on for three key tech areas in which engineers are having a big impact.


Robotics is an area which is being heavily invested in by many different types of industries, and engineering is no different. One of the most exciting projects under development is a robotics system called “visual foresights.” While usually robots react to data in real time, responding to things as they happen, researchers at the University of California are working on making it possible for robots to imagine the future based on their actions.

This will mean that the tech will be able to interact proficiently with situations or items they haven’t seen before. For instance, they might be able to predict what their in-built cameras will see if they perform, in a set sequence, a certain set of movements.

At the moment, the predictions robots can make through this visual foresight are only quite limited, and reach into the future by just a few seconds. However, this step forward means that robots can now, and will soon be better able to, learn to perform jobs without having any prior knowledge, or help from humans. This will in turn open up a whole new avenue for how and where robots can be utilized.

3D Printing

Another topical subject is 3D printing. It is also going ahead in leaps and bounds, particularly when it comes to use in medicine. For example, 3D-printed anatomical models are being used more and more to help doctors improve the outcomes of their surgeries. This is because the models help surgeons to practice operations (on specially-created replicas of patient organs) in advance.

While these models have until recently been made of hard plastic, have a different feel to real living tissue, and are tough for surgeons to cut into, things are changing. A team of researchers led by the University of Minnesota has been developing 3D-printed organ models which are more advanced than the older plastic ones.

The new versions actually have the same feel and mechanical properties as living tissue. They’re also better because they can come equipped with soft sensors to provide feedback during practice options. This enables medicos to know when they’re applying the right amount of pressure without damaging fragile tissue. It also makes it easier for surgeons to plan surgeries effectively, and to predict how patient organs will react to and heal from operations. Eventually it’s believed that bionic organs may be able to be printed on demand as required for transplants.

Another big 3D project in the works is the creation of printed objects which can connect to Wi-Fi without the need for electronics. At the University of Washington, teams are developing 3D-printed items, made from plastic, which can connect and talk to, and collate data from, other devices in a building. This is done via the internet, but without the usual need for electronic components.

The engineers at the University replaced some of the electronic functions typically performed by components with mechanical motion with pieces which can be 3D printed. This list includes buttons, springs, knobs, switches, and gears. It is hoped that consumers will one day be able to use their own, domestic 3D printers to create objects out of readily-available plastics, and have these devices communicate wirelessly. For example, a bottle of laundry detergent could sense when the soap is getting low, and automatically connect to the internet to order a refill.

Biomedical Advances

Biomedicine is another exciting field. Apart from the aforementioned 3D-printed organs, engineers in are working on many other developments.

A team of researchers at the University of Texas, in conjunction with others at the University of Reims, are concentrating on complex plasmonic nanovesicles. This is the term for minute capsules which can be taken as a pill. Once swallowed, they navigate the bloodstream and move to a set location in the body to deliver a drug in the exact spot where it’s needed. By hitting the pills with a short laser light pulse once they’re positioned, the researchers believe the nanoparticles will change shape and release their contents on demand.

This innovative drug-delivery system has enormous potential and could truly transform medicine. This is especially the case in the treatment of cancers and the study of the brain, where only certain parts of an organ need to be targeted.


5 questions for… Roger Davies, Value Management Guru

Roger Davies is a business consultant and author. His specialist topic is Value Management — that is, ensuring that business transformation delivers on the goals it sets out to achieve. He’s also an old colleague and friend — we worked for the same consulting firm, back in the Nineties.

I caught up with Roger to get an update on the latest thinking on how we define the value of our business change programmes.

1. What the heck is ‘value’ anyway, and how does it relate to money? You once told me value equated to “benefits minus costs” — is it still this simple?

Yes it is that simple. The challenge is how to frame value so that this ‘Value Equation’ works in any context and when the units of benefits and costs are not the same. Value is most effectively framed as energy transformation. Money is effectively a surrogate for energy, and money transactions the mechanism for energy transformations – an invention up there with the wheel in terms of energy transmission. That is why it is called currency, because it is all about the flow.

Therefore, it is more appropriate to frame money as a measure of value for the purposes of transaction – i.e. the informational means by which energy can be transformed through value chains. Money helps us define the value of a relationship, a transaction or a situation. The concept of money works very well under near perfect competition where choice can (but not inevitably) create equitable balance, reflected in cost and price – i.e. costbase and revenue, the 2 sides of the P&L.

2. Where does use of money to define value fall down?

Whilst money is an efficient tool for transaction, research shows us that it is an unreliable indicator of value. Symptoms of this include excessive C-level salaries at one end and at the other, the ‘gig’ economy and aged care, where substantial value is often delivered by people on subsistence income. So when money is used as a direct synonym for value, we come unstuck.Whilst money is an efficient tool for transactions, research shows us that it is an unreliable indicator of value. Symptoms of this include excessive C-level salaries at one end and, at the other, the ‘gig’ economy and aged care, where substantial value is often delivered by people on subsistence income. So, when money is used as a direct synonym for value, we come unstuck.

3. So, shouldn’t we look for other ways of measuring value?

The brutal reality is that money drives the physical world which we have created, so we either change the model (tricky) or define and frame value using money in a way which drives the right stakeholder outcomes, taking into account its limitations. My stance is not to declare dogmatically that everything can be measured directly in financial terms, but that through precise tracing of cause and effect, it is possible to determine how intended outcomes can be delivered with equitable return to all stakeholders. In other words, quantify the benefits to the decision makers in the units they need to deliver win-win outcomes to all stakeholders , This requires a very different approach, not right or left wing dogma but precise causal thinking.

4. Ok, but Wwhat does this mean for organisations looking to ‘deliver’ value?

The answer is two-fold. First you should use money where appropriate, and other measures where not. And second, you can see money as the cart, not the horse — which is vision and strategy. For example, in the case of aged care, you can start with the highest purpose – ‘people living comfortably and in dignity in their later life’. You can then work backwards through the value chain to determine how all the players, including tax payers, investors, society as a whole, can gain from the attainment of this purpose through the performance they deliver.

5. This sounds quite complicated — can’t I just say, “Here’s a problem, what’s the solution, how much does it cost?”

This quantification cannot be achieved using conventional linear thinking and static models. Indeed, it’s precisely this kind of thinking that leads so many projects and programmes to under-deliver. If we really want to deliver benefits to our organisations, we are directed to master the world of complexity and systems thinking, where causality exists in patterns and probabilities, with many soft drivers, such as trust, security, relationships etc – which boil down to values.

This quantification cannot be achieved using conventional linear thanking and static models. Indeed, it’s precisely this kind of thinking that leads so many projects and programmes to under-deliver. If we really want to deliver benefits to our organisations, we are directed to master the world of complexity and systems thinking where causality exists in patterns and probabilities, with may soft drivers, such as trust, security, relationships etc – which boil down to values.

This may sound like it’s over-complicating things but the fact is, too many projects today work on the basis of throwing money at the problem, rather than thinking about how to ensure the solution delivers value. Accordingly, Value Management places great emphasis on non-linear causal modelling of Complex Adaptive Systems, such as markets, to quantify the linkage between programme deliverables (interventions) and stakeholder outcomes.


My take

In an industry driven by cycles of telling the world that the latest raft of technology can achieve less with more, it’s important for all enterprise decision makers to resist any urge to accept these mantras. At the same time, thinking about value as opposed to money is a challenge: while the latter is tangible, the former is amorphous and, not ironically, a harder sell.

As a result our business cases tend to be linear, talking in terms of TCO or ROI over a fixed period. And meanwhile, we struggle with concepts such as ‘digital transformation’ — business leaders know they have merit, but can’t put their finger on what it is.

The answer, like it or lump it, is to tease apart the link between value and financial measures: as Roger suggests, use money when appropriate, but not when it isn’t. It is incumbent on any strategist to know the difference between value and money, and be able to drive better business decisions as a result.

5 questions for… Aware by Wiretap

Wiretap is a purveyor of “collaboration tool monitoring and governance” solutions, a.k.a. software that can scan the messaging and files within a collaboration platform. Its flagship product, Aware by Wiretap, monitors all content, including private messages and the content of files, shared with both internal and external members of platforms such as Yammer, Workplace by Facebook, Slack and Microsoft Teams, and send alerts in the case of a ‘toxic employee’ or policy breach.

In these five questions, I wanted to know what was behind the need — that old question of, is this a product or a feature; what’s net-new vs re-facing and renaming older solutions, and so on. And also, frankly, because I was intrigued by the name!

1. I see Aware by Wiretap as DLP applied to collaboration platforms, what did I miss? 

Aware by Wiretap does have some underlying DLP capabilities as it relates to your collaboration platforms, but goes beyond your traditional DLP, as it provides external and internal compliance governance that does more than security-focused DLP. Aware avoids impacting the intended experience of the platforms by running in the background. The platform utilizes Wiretap’s proprietary, enterprise-specific AI models, and provides human context by giving your organization insight into employee behavior, such as message sentiment. You can determine if it was a malicious or an accidental occurrence – and you can even educate the user about proper protocol automatically through the platform.

2. In Venn diagram terms, what is the size of the problem that Aware by Wiretap is looking to solve, e.g. relative to email, web site breaches?

The enterprise collaboration market is expected to grow to $70 billion by 2019 but little thought has gone into monitoring solutions to allow organization wide adoption, especially in highly regulated industries. In fact, many organizations have multiple collaboration platforms inside the company at any given time. While we protect against some external threats, we’re primarily focused on the insider threat detection as it pertains to collaboration security and compliance. As such, we offer a centralized point of governance across the platforms – organizations only need to use one dashboard, one set of policies, one set of actions, to govern multiple collaboration tools.

3. You make a thing of encouraging positive interactions — how do you square the intrusion and overhead vs protection and improvement circle?

Employee monitoring has existed for decades — we generally expect mail, email and voicemail, and HR-related information to be the property of our employer. Generally, people don’t enjoy not being ‘fully trusted’ by our employer; but we don’t always connect the dots between monitoring as a workplace necessity, and its role in protecting employees from situations such as sexual harassment, inappropriate communication, threats, rumors, and a toxic culture.

Inappropriate messaging doesn’t just put the company’s reputation at risk, it can also hinder productivity. For example, if a female engineer is propositioned and harassed by her boss on the company’s collaboration network, which was installed and intended to spur collaboration and innovation, how can she possibly be compelled to participate on that network? Also consider that this employee may not report the behavior due to the fear of retribution. The reality is companies must provide a safe, compliant and secure environment for employees, customers and other stakeholders in order to enable positive collaboration and fully realize the benefits of the investment.

4. How does Aware work in a mobile context?

We monitor the collaboration platform, regardless of how users connect to the platform. Our implementation method not only allows mobile coverage, but easy installation (hours not days) and time to value for an organization.

5. What specifics of GDPR are you looking to address with your data management module?

The Aware Data Management Module provides tools to help organizations address several GDPR provisions as it pertains to a company’s collaboration platform. This includes Article 5’s principles for processing of personal data, as well as Article 12 (on transparency of use), 15 (right of data access) and 17 (right to erasure/right to be forgotten).

6. And a bonus question: is the company name deliberately ironic/controversial/honest?

Deliberately provocative! It was important for our name to be memorable particularly in our early stages when we focused more on security. Now that we focus more on employee behavior, compliance and culture protection, we’ve started to soften the tone and relaunched the product as Aware by Wiretap late last year. Our product name is on a journey alongside the platform. As we continue to add features and evolve the platform to add value across organizational departments, we’ll continue to look ahead at the roadmap and evaluate the most appropriate name.

My take

Wiretap sits in an interesting zone somewhere between function and platform. As long as there are evolving events and contexts to monitor, we will need capabilities that focus on the monitoring, alongside the products and services that do the ‘core’ work — such as collaboration. Wiretap’s use of AI — in this case, natural language recognition and rule modelling — is perhaps the most intriguing element here as it aligns with the evolution of platforms such as Slack, with their use of bots and other AI-driven automation. There’s nothing to stop Aware being used for broader handling of events (indeed, Wiretap says it is already being used to recognize helpdesk requests) — which moves the product into the broader category of AI-based collaboration support.

As ever, it’s important for smaller vendors such as Wiretap to stick to their knitting: however generic the solution can be, vendors with a clever algorithm who say “well, it can be used for anything” tend to find themselves out on a limb. As the collaboration space evolves however, vendors such as Wiretap may find themselves being drawn into new areas by market need.

In the meantime, it is a fact that the success of collaboration tools has not been paralleled by security and compliance protections: indeed, some of the success of tools like Slack and so on could be put down to the fact that they are less encumbered than traditional collaboration mechanisms (email and the like). While this means Wiretap is filling a necessary gap in the market, it may also be a reflection of the state of maturity of collaboration today.

For IT decision makers, Wiretap may well respond to a problem — either to resolve a risk/challenge with inappropriate use of messaging, or to demonstrate that collaboration behaviors are conformant to corporate policy or indeed, regulation. Even if this is the case, use of a product such as Aware by Wiretap should still be considered within an overall framework of acceptable use policy, training and awareness across the employee base.




5 questions for… TechVets

TechVets is a newly launched social enterprise in the UK, which “provides a bridge for veterans and service leavers into cyber security and technology.” Its goal is to help ex-forces personnel to start careers in Civvy Street, both with direct activities and by catalysing a network of service leavers and industry representatives. TechVets’ first support programme is a Digital Cyber Academy from Immersive Labs, offering free Cyber-Security training to the first cohort from the service leaver and veteran community.

I attended the launch event and spoke to a number of people, and the below is an amalgam of what I read, saw and heard.

1. Why is TechVets necessary?

Simply put, the transition between the forces and civilian careers is not as simple as it could be. While service men and women have a wealth of highly transferrable skills, they can struggle to find their way into the tech industry. This is primarily down to a lack of connections. At the same time, the industry stands to gain. With effective transition support, veterans have the potential to contribute an enormous amount to the future of the UK’s tech, cyber security and startup sectors.

2. What’s so different about the corporate environment?

Part of the challenge is about translating the capabilities of technology into positive business outcomes. It’s less about solving problems and making things happen, and more about helping identify opportunities and helping people achieve more. In addition the corporate life is more diverse — this isn’t just about gender, race or sexuality, but also about diversity of thought. This latter point is a strength, but it also creates a challenge for people used to more structured thinking.

3. What can the industry gain from ex-military staff?

People that have worked in the military bring a number of soft skills that are vital in the corporate environment. Standard military training makes people problem solvers, and able to both follow standard procedures and follow initiative when the situation becomes more taxing. There’s also a level of inherent trust — people who are ethical, reliable and who can be trusted. Thinking specifically about technology — forces staff are used to using technology to deliver solutions, rather than seeing it as an end in itself. In compliance-based environments, ex-forces personnel are very good at risk analysis and mitigation and can build on that.

People that have worked in the military bring a number of soft skills that are vital in the corporate environment. Military personnel have very strong people skills, with experience of both being led and of leading. They understand the notions of tempo and scale — to work at the pace and size of the challenge — and are also tuned into the notion of training. And also, strangely, there’s a sense of humour in the forces that doesn’t exist so much in corporate life. Yes, it’s a bit dark at times but it really helps if a real crisis hits, not just to alleviate the mood but also to help communications.

4. But what are the main challenges?

Culture shock is a major issue — in corporate life, most people don’t do what they are asked! Companies talk a lot about strategy and values but do they live them? In the military you are used to walking the talk, which isn’t always true in the enterprise!

Equally, the corporate world may be looking for certain things from their potential hires — for example, expecting a post-graduate degree. For people leaving the military and who are unsure what they want from civilian life, the need to knock on doors, to market oneself and indeed, to demand a market wage, can feel more than daunting.

5. So, what should ex-military people be thinking about?

Of course, it’s going to take time to adjust. You may leave the services but the services do not have to leave you — you bring a great deal to the table in terms of the experience you bring.

As a starting point, you should think about what you do (and don’t) want to do. You may be good generalist but the industry tends to look for specialists first. Think of an interview as a situation to be dealt with, and plan for it. For example, think about competencies, about what are the expectations of the situation and what you can do to deal with them.

And of course, use your network — and find out from them what works and what doesn’t. You can’t be expected to have everything on a plate, it is up to you to demonstrate this to future employers, and to take responsibility for your own future.

My take

I’ve not been in the military but having worked with many ex-service personnel, in various government establishments, I’m aware of the challenges that face people shifting from one well-established culture to another. Often the issue comes from a strange feeling that skills learned in the military are irrelevant, redundant or inadequate for the needs of corporate life.

This feeling is misplaced, as a significant opportunity exists to take advantage of this unique skills source. With technology in general, and cybersecurity in particular being areas that continue to grow, ex-forces staff should not underestimate the value that they bring to the table. At the same time, yes, there is a culture shock that needs to be addressed. An ex-military colleague told me of the benefits of mentoring, particularly if the mentor comes from a similar area of the forces.

At the launch event, repeated stories were about how finding a stable career offered a response to depression and in one case, near-suicide. Ex-forces personnel can struggle to get on in civilian life, to the extent they can end up homeless — numerous charities exist in the UK, the US and elsewhere to support such people, illustrating the problem. The bottom line is, we can’t underestimate the importance of initiatives such as this.

For most firms GDPR is an opportunity, not a threat

Many conversations around GDPR seem to follow a similar sequence as Dave Lister’s experience in the opening episode of Red Dwarf.

Holly: They’re all dead. Everybody’s dead, Dave.

Lister: Peterson isn’t, is he?

Holly: Everybody’s dead, Dave!

Lister: Not Chen!

Holly: Gordon Bennett! Yes, Chen. Everyone. Everybody’s dead, Dave!

Lister: Rimmer?

Holly: He’s dead, Dave. Everybody is dead. Everybody is dead, Dave.

Lister: Wait. Are you trying to tell me everybody’s dead?

So, yes, GDPR affects all kinds of data. Big data, small data, structured and unstructured data, online and offline, backup and archive, open or grey, digital or paper-based data. It’s all data, and therefore GDPR applies to it.

This simultaneously makes the task of GDPR compliance very easy, and very difficult. Easy, because decision makers don’t have to worry about what data is involved. And very difficult, because few organizations have a clear handle on what data is stored where. That filing cabinet in the back of a warehouse, the stack of old tapes on top of a cupboard, that rack of servers which were turned off… yeah, all of them.

Because that’s not the focus of GDPR, you know, the technology gubbins, complexity and all that. The regulation quite deliberately focuses on personally identifiable information and its potential impact on people, rather than worrying about the particular ramifications of this or that historical solution, process or lack of one.

At the same time, this does suggest quite a challenge. “But I don’t know what I have!” is a fair response, even if it is tinged with an element panic. Here’s some other good news however — laws around data protection, discovery, disclosure and so on never distinguished between the media upon which data was stored, nor its location.

You were always liable, and still are. The difference is that we now have a more consistent framework (which means less loopholes), a likelihood of stronger enforcement and indeed, potentially bigger fines. To whit, one conversation I had with a local business: “So, this is all stuff we should have been doing anyway?” Indeed.

Of course, this doesn’t make it any easier. It is unsurprising that technology companies and consulting firms, legal advisors and other third parties are lining up to help us all deal with the situation: supply is created by, and is doing its level best to catalyse, demand. Search and information management tools vendors are making hay, and frankly, rightly so if they solve a problem.

If I had one criticism however, it is that standard IT vendor and consulting trick of only asking the questions they can answer. When you have a hammer, all the world is a nail, goes the adage. Even a nail-filled world may seem attractive for purveyors of fine hammers, they should still be asking to what purpose the nails are to be used.

To whit for example, KPMG’s quick scan of unstructured data to identify (say) credit card numbers. Sure, it may serve a purpose. But the rhetoric — “Complete coverage, get in control over unstructured data on premises and in the cloud.” implies that a single piece of (no doubt clever) pattern matching software can somehow solve a goodly element of your GDPR woes.

As I have written before, if you want to get there, don’t start from the place which looks at data and says “Is this bit OK? What about this bit?” A better starting point is the regulation, its rules around the kinds of data you can process and why, as documented by the Information Commissioner’s Office (ICO).  The “lawful bases” offer a great deal of clarity, and start discussions from the right point.

Mapping an understanding of what you want to do with data, against what data you need, is not cause for concern. In the vast majority of cases, this is no different to what you would do when developing an information management strategy, undertaking a process modelling exercise, or otherwise understanding what you need to do business efficiently and effectively.

The thing GDPR rules out is use of personal data people didn’t want you to have, to fulfil purposes they didn’t want you to achieve. For example, use of ‘cold lists’ by direct marketing agencies may become more trouble than it is worth — both the agency, and the organization contracting them, become culpable. Equally, selling someone’s data against their will. That sort of thing.

But meanwhile, if you were thinking of harvesting maximum amounts of data about, well, anybody, because you were thinking you could be monetizing or otherwise leveraging it, or you were buying data from others and looking to use it to sell people things, goods or services, you should probably look for other ways to make money that are less, ahm, exploitative.

But if you have concerns about GDPR, and you are ‘just’ a traditional business doing traditional kinds of things, you have an opportunity to revisit your information management strategy, policies and so on. If these are out of date, chances are your business is running less efficiently than it could be so, how about spending to save, building in compliance in the process?

Across the board right now, you can get up to speed with what GDPR means for the kind of business you run, using the free helplines the regulators (such as the ICO) offer. If you are concerned, speak to a lawyer. And indeed, talk to vendors and consulting firms about how they are helping their customers, but be aware that their perspective will link to the solutions they offer.

Thank you to Criteo and Veritas, whose briefings and articles were very useful background when writing this article. As an online display advertising firm, Criteo is keenly aware of questions around personal vs pseudonymous data, as well as the legal bases for processing. Veritas offers solutions for analysis of unstructured data sources, and has GDPR modules and methodologies available.