Vincent Bieri, Chief Product Evangelist & Co-Founder, Nexthink
Ok, so we know about digital transformation. Whether it’s creating a competitive advantage, stimulating new sources of revenue or optimising costs, there’s no getting around the endless march of progress. An entire company’s value chain can be swept along with the effective implementation of digital technologies.
But where do employees feature in all this?
With lots of changes in working methods, organisation and tools, is constant digital transformation really working for employees? On the surface, it is. Everything suggests that digital tools, in the broad sense – connectivity, mobility, video conferencing, intranets, the latest collaborative applications – make employees more efficient while providing greater ease of use. But there’s a catch. Digital transformation can only deliver on its promise if digital tools work 24/7 and employees adopt and use them optimally. And that’s another story.
What the IT department measures is not what the user feels
A slow laptop start-up, Skype crashing repeatedly, Outlook not functioning correctly – these are all events which IT management is not always aware of despite them disrupting users and directly affecting productivity. Why? Because IT management mainly uses service level agreements (SLAs) to measure the quality of the services they deliver to the business. An SLA can show the state of business systems to be good (applications, network, servers), while not necessarily being indicative of the actual user experience. Network dashboards might display a 99.9% uptime while a user can at the same time, notice a slowdown in their inbox that has nothing to do with a network problem.
In other words, IT teams only see the tip of the iceberg. Problems are only discovered after issues are reported to the support service, which they not always are. Any attempt by users to resolve the problem themselves affects productivity. Once contacted, it may still take hours for the service desk to solve the issue. All these delays result in lost time – Robert Half estimates that up to 22 minutes of employee productivity are lost a day to IT issues.
The employee has become a consumer
To make matters worse, the profile of IT users has changed. More autonomous and more demanding, today’s employee is above all a consumer. They make full use of digital technology in their day-to-day life to get their shopping delivered, book a ticket for a show or do their banking, and they expect a similar experience when they use the digital tools available to them in their professional environment.
This phenomenon is even more pronounced among the young talents of Generation Y. More than ever, employees are the internal customers of IT management who must be understood and provided with tailored services and digital tools. A standardised approach to IT is no longer appropriate because there are almost as many IT experiences as there are employees. Each employee has their own expectations and preferences according to the requirements of their job, their work habits, and even their personality. The time has come to tailor IT services according to the needs of differing users.
The importance of the human factor
Ironically, while IT management is introducing transformation initiatives to improve business functions, the side-effects of these changes are undermining users’ ability to manage their IT. If new IT resources do not function as expected, or are difficult to use, employee frustration can grow quickly. Furthermore, some tools might not be adopted as intended by management, or not utilised correctly.
This matters because your people can have a marked impact on the success or failure of your digital transformation projects.
In light of this, what can IT management do to ensure that employees are supporters of digital transformation projects, and not the major obstacle to its implementation?
Placing user experience at the heart of the IT value chain
For Nexthink, measuring the user experience is based on two strands: firstly, measuring the workstation’s technical health (boot time, latency, memory used, position compliance score) and secondly, measuring users’ perception. As we have discussed, SLAs provide a solid way measuring and responding to technical matters, but are inadequate when trying to qualify the second category. To truly have a 360-degree view of the quality of user experience in an organisation, we must also analyse in terms of XLAs: ‘Experience Level Agreements.’
All too often we forget that behind each workstation is a person whose feelings and motivation set a company culture which can have a huge impact on the success of your business and your ability to retain valuable employees. Take the example of a print job that suddenly takes ten minutes rather than thirty seconds. From a purely objective point of view, this increased response time may seem alarming. But for the user, it is also a frustrating distraction
In order to collect subjective data from users about how employees are utilising technology in their work life, employers must deploy simple feedback and engagement tools similar to ideas seen in the B2C sphere.
It’s all a question of timing
Engaging employees starts with unobtrusively giving them the right information at the right time.
A common example that combines the focus on XLAs and SLAs is a pop-up message that informs the user that an issue with their workstation has been detected. From this the user can be asked if they agree to the IT department implementing a fix which will require a computer restart. The user can choose whether the time is right or not. As another example, imagine that a user has had more than 5 consecutive Skype for Business crashes in the last 24 hours. Once the incident is resolved, the IT team can trigger a pop-up on the user’s workstation to ask them to check that everything is in order. This type of interaction has two advantages. Firstly, the IT department confirms that the actions taken have indeed produced the desired effect by asking the user directly. Secondly, as the interaction is quick and in the right context, the probability of a response from the user is much higher. Bingo, the employee is ‘engaged’!
Engagement: the cornerstone of success in digital transformation
Interacting with users at the right time and in the right context accelerates the take-up of new tools introduced by digital transformation. It is one thing to roll out new software, it is quite another to make sure they are being used to their full potential. Digital Transformation is only transformative if employees use the upgraded resources. Achieving this is about adequate support and teaching best practice. It is also making them aware when a specific behaviour or misuse risks affecting the performance of a service, such as using Skype through a VPN.
It’s time for IT management to put user experience at the centre of its value chain, just as brands have made full use of digital technology to put the end consumer at the heart of theirs. Engaging employees helps to create the conditions for a quality digital experience which increases productivity and employee satisfaction. Management solutions for the digital experience, help support the company’s digital transformation trajectory and position IT management as a contributor to business growth.
DISPELLING BIOMETRIC MYTHS AND MISCONCEPTIONS
By Lina Andolf-Orup, Head of Marketing at Fingerprints
Gangsters cutting off enemies’ fingers to access secret locations and spies lifting fingerprints from martini glasses – the imagination of the entertainment world has been running wild ever since biometrics entered the scene.
Couple that with the limitations of some early biometric solutions from fifteen years ago, still anchored in the minds of many consumers, and you have the perfect recipe for an apprehensive and uncertain public.
Thawing lukewarm attitudes with a biometric touch
The biometrics industry has made great strides in the last few years – something particularly true for smartphones. Fingerprint authentication has replaced PINs and passwords as the most popular way to authenticate on mobile, with 70% of shipped smartphones now featuring biometrics.
And it doesn’t end there. Many adjacent markets are now eager to benefit from the secure and convenient authentication solutions that biometrics offer. Take the payments industry, for example, where biometrics payment cards are currently gathering real momentum.
However, some consumers are still uneasy about accepting biometrics. A recent study found that 56% of US and EU consumers are concerned about the switch to biometrics as it’s not enough understood to be trusted.
Although attitudes are shifting for the better, stats like this demonstrate there is still some work to do to disprove common biometric myths and showcase just how smart today’s solutions really are.
Dispel, adopt, repeat
The evolution in consumer biometrics in the last two decades has been phenomenal. And today’s solutions are far more advanced and safe than many may think.
To help bring an end to the myths, let’s expose some of the most common misconceptions around biometrics.
Myth: Biometric data is stored as images in easy-to-hack databases.
A leading myth about biometrics is that when a fingerprint is registered to a device, it is stored as an image of the actual fingerprint. This image can then be stolen and used across applications. In reality, the biometric data is stored as a template in binary code – put simply, encrypted 0s and 1s. Storing a mathematical representation rather than an image makes hacking considerably more challenging. In most consumer applications, this template is also not stored in a cloud-based location, its securely hosted in hardware on the device itself for example in the smartphone, in the payment card. Thus, it stays privately with its owner.
Myth: Fingerprints can be easily replicated to ‘trick’ devices.
The internet is full of articles and videos that claim it is possible to use materials from cello tape to gummy bears to craft fingerprint spoofs and access biometric systems. Although there may have been a time where gummy bear spoofing was the go-to party trick, todays’ consumer biometric authentication solutions have too many technological defences, such as improved image quality and matching algorithms, to simply ‘trick’ devices. Plus, on top this, the criminal needs to have access to the person’s device where this fingerprint is enrolled e.g. smartphone, payment card, before he/she notices and blocks it. This is not scalable nor common, in comparison to gaining access to someone’s PIN code or skimming a contactless card.
Myth: Physical change will prohibit access to my device.
Although our irises don’t change as we age, our fingerprints can and our faces will. Does that mean we have to update our biometric devices every few months to capture these changes? Not quite! Unless there are drastic, sudden changes, the ‘self-learning’ algorithms in modern-day biometric systems are able to keep up with our developing looks.
Who you gonna call? Mythbusters!
These are just some of the common biometric myths and misunderstandings perpetuating in consumer mindsets. Thankfully, though, while we’re working hard to rid the world of the myths, belief in the value of biometrics is only expected to grow. But as solutions expand and diversify, the myth-busting fight will continue.
Fingerprints has been a leader of innovation in biometrics for the last two decades. We’re proud of the expertise and R&D we’ve been able to pour into our biometrics solutions to deliver stronger security and a better user-experience. To learn more about the most common biometric misconceptions and the modern-day technology that allows us to dispel them, download our eBook here.
WHAT EVOLUTIONARY AI MEANS FOR FINANCIAL SERVICES
by Babak Hodjat, VP of Evolutionary AI at Cognizant
Many banks and other financial services institutions (FIs) are beginning to recognise the benefits of AI-driven solutions as a way to get ahead in the market and challenge the competition. Amongst many other benefits, the technology enables organisations to offer hyper-personalised customer experience, dramatically improve internal decision making, and drive operational efficiency. However, many businesses are struggling to move beyond the experimental phase and reach actual AI deployment. It is those organisations that are at risk of being left behind.
The financial world has already been transformed by AI, and this transformation is continuous. A new breed of AI, known as ‘evolutionary AI’ has begun to further accelerate innovation. It is capable of automatically designing itself with little need for explicit programming by humans – innovatively creating complex AI models, and optimising decisions considering multiple scenarios.
This technology is revolutionary for industries across the world, but in particular it is set to transform the financial services sector. Enabling businesses to spot novel strategies that would never have been identified by human data scientists, and, in turn, allowing companies to take full advantage of today’s massive data sets – evolutionary AI will soon be a vital tool in all FIs’ arsenals.
The nuts and bolts of evolutionary AI
Emerging technologies that enable AI algorithms to design themselves are allowing organisations to transcend human limitations. Evolutionary AI operates iteratively. Firstly, it randomly generates a set of potential solutions to form an initial population and assigns a score to each solution based on how well it performs relative to other solutions. In the second round, it retains the solutions that performed best, perhaps only 5% of the total, and recombines their components, sometimes “mutating” them to create a new population. This new population is then tested, and the process begins again. Over multiple generations, the appropriate components of the more successful solutions become increasingly prevalent in the population, and eventually a solution is discovered that yields the best outcomes.
Advantages and use cases
Compared to human design, evolutionary AI can be deployed far more quickly, avoids biases and preconceptions, and typically performs better. Furthermore, the chosen model will evolve and improve over time based on new data.
Evolutionary AI can be applied in a wide variety of areas at FIs. Some examples include designing quantitative trading strategies to maximise returns while minimising risk and loan underwriting. Rather than relying on human analysis, evolutionary AI solutions can quickly analyse all the combinations of relevant variables to create models that more accurately assess the risk of default by a potential borrower.
A recipe for success
In order to reap the benefits of the technology, FIs should focus on the following:
- Responsible AI – Behave in ways that make customers and employees comfortable, i.e. not making decisions that are unethical or exhibit bias. Companies need to monitor them to ensure they continue to act appropriately, as they learn and evolve.
- Viewing AI through a business lens – Having AI projects managed by cross-functional teams with business executives in the lead is a good place to start. Companies also need to look across their organisations to identify opportunities to generate concrete business value from AI — not only in reduced costs but also in boosting revenues by delivering enhanced customer experiences and through improved decision-making.
- Enhance data management – AI applications depend on access to timely and accurate data, which is a challenge for many FIs that have fragmented data architectures with multiple legacy systems. Companies need to identify which types of data are required for each AI project and ensure they can be captured in an appropriate format.
- Approach with speed and caution – AI projects need to be rolled out quickly, while at the same time be rigorously measured, so failures are terminated promptly while successes are moved into production.
The sophistication of AI technology is set to significantly improve over the coming years as it continues to design and test itself. As a result, it will become more critical to the productivity of FIs, and soon businesses will recognise it as a vital tool for consulting on important business decisions. It will not be long before humans and AI are working alongside each other, with robots handling routine tasks, enabling employees to focus on more complex and sensitive activities. Delivering more value together than either could on their own.
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