If you do a search for “Digital Transformation,” you will, no doubt, be overwhelmed by the sheer number of blogs, books, research papers, and trade conference presentations that cover some aspect of the topic. Experts and thought-leaders continue to share insights intended to help make sense of the many disruptive forces that are shaping the global economy. But with such a broad subject, it’s often difficult for any one article or discussion to give a comprehensive overview that’s easy to digest.
Chuck Martin has done just that.
Martin’s book, Digital Transformation 3.0: The New Business-to-Consumer Connections of the Internet of Things, brings together a wealth of research from a variety of respected sources to lay out a perspective on the digital landscape of today, including predictions about where things are heading in the next few years. In addition to being impeccably sourced, the inferences and conclusions that Martin draws from the aggregated research add thoughtful commentary that elevates the book from merely being a collection of observed trends to something that is, without a doubt, more than the sum of its parts.
The underlying premise of the book is that we are witnessing the third phase of digital transformation.
Just as digital transformation is a broad and deep topic, so is the discussion of the IoT. Martin provides a framework in which to segment the discussion, identifying what he sees as the seven technologically-driven forces that compose the IoT landscape: sensors, artificial intelligence, voice assistants, smart homes, virtual and augmented reality, connected cars, and drones and robots.
The author dives into each of these areas in detail, emphasizing the unique factors of each of these technologies that are shaping the way people interact with each other, with businesses, and with the smart devices around them. He also highlights the combinatorial effect that these forces have on each other. “Rather than being one cohesive, end-to-end phenomenon,” Martin writes, “the Internet of Things comprises differing silos of major innovation.” These silos interact and interoperate to propel user experiences forward, often by leaps and bounds.
The focus of the book, as the subtitle suggests, is largely about the consumer-to-business relationship. However, it seems clear that many of the observations that Martin makes could be readily applied to the relationship between employees and employers. The influx of IoT devices into people’s lives will likely, as Martin says, begin to change consumer expectations for how they interact with business. It stands to reason, however, that these expectations will carry over into the workplace, too. A careful reading of the book with an eye toward the evolution of the digital employee experience can yield insights that go beyond the explicit predictions and observations found in its pages.
Martin’s chapter on smart homes, for example, can be easily expanded to a discussion of smart workspaces, as some of the same opportunities for personalization, efficiency, and automation exist in both scenarios. Similarly, the discussion of VR and AR easily translates to an employee experience discussion, with the author actually referencing examples of employers using AR techniques to train their workers to perform tasks. The future of work will be impacted heavily by these forces, and businesses should pay attention to how these consumer trends inform new ways of working.
Such subject matter might seem somewhat dry and a bit dense to process, but this book shines when the author tries to imagine scenarios from the not-so-distant future, in which IoT devices significantly change our experiences. In one example, Martin lays out some theoretical (yet highly plausible) conversations with a digital assistant (such as Alexa, from Amazon) in which brief, natural conversations yield significant, complex outcomes beyond what are currently possible. It’s thought-provoking and engaging, and it enjoins the reader to consider what is now (or will soon be) possible in a way that’s interesting and fun.
Chuck Martin succeeds in covering a lot of ground in what amounts to a fairly quick, easy read. Digital Transformation 3.0: The New Business-to-Consumer Connections of the Internet of Things is well worth your time and will undoubtedly provide much food for thought.
There has been much discussion over the past few years regarding illusive productivity gains in the face of the widely touted transformative benefits springing from the current generation of digital technology (often labeled under the moniker of “SMACIT” – for social, mobile, analytics, cloud, and internet of things). Economists have repeatedly observed that economic growth has been much weaker than expected given the impact that digital technology is having on the economy, both in regards to enabling new business models and driving changes in social behavior.
Historically, we’ve seen this before – in the 1970s and 1980s economists coined the term “productivity paradox” to describe the condition where economic growth slowed at the same time that information technology was being rapidly integrated into business operations. Nobel Prize-winning economist Robert Solow quipped in 1987 that “you can see the computer age everywhere but in the productivity statistics.”
However, there was a subsequent acceleration in productivity and business growth in the late 1980s and an even more lively burst in the early 2000s. While there is debate about the drivers, nature, and degree of this growth, there is no doubt about the dramatic degree of organizational restructuring and downsizing undertaken during these periods.
We’re not going to wade into the academic debate regarding fundamental economic forces. However, we will posit that much of the restructuring and downsizing was enabled by technology – tremendous cost was removed in organizations as middle management was replaced with tools for analysis, processing, and communication, among many other capabilities. This in turn drove productivity gains.
Therefore, when economists observe today that the SMACIT-driven digital revolution has failed to impact productivity significantly, we wonder if a new perspective on organizational dynamics is needed.
Perhaps legacy businesses are, for the large part, still adapting organizationally by way of the old models of efficiency and operational excellence, mostly in an incremental manner – this means redesigning processes, structures, jobs, and skills. Some businesses are also grafting digital businesses onto established business operations or creating “digital native” organizations as skunkworks – placed at arms-length in the business units and not upsetting the traditional order.
What most legacy companies have not yet done is undertake a deep exploration of how they must fundamentally change across the enterprise in response to the new forces of internet era-based digital technology. Technology no longer simply replaces work or provides better tools – technology becomes inextricably comingled with human activity, therefore shaping new behaviors. This must be understood in the larger context of business and work design – not as a bolt-on but as a new way of thinking about work.
This technology offers much more than the prior era’s propositions of faster, cheaper, and more convenient. For example, Uber has developed innovations in business models and social and mobile technologies that are profoundly different from the more focused operational innovations of web retailers at the beginning of the century.
Recent industry surveys, such as the 2017 CEO Challenge study from the Conference Board, demonstrate that CEOs and other executives recognize the economic imperative for such profound change. However, businesses are not prioritizing “digital transformation” for the near-term (i.e., next two years).
Why is this the case, and what would change these conditions? We feel the priority is not yet high for two reasons:
Regarding consensus, barriers can be addressed by building shared perspectives on relevant technology and market forces and identifying high-impact, lower-risk actions; for example, in developing a focused set of organizational capabilities at the enterprise level tied directly to digital business strategy. Examples of this include capabilities for creating and sharing knowledge and expertise and for defining and making actionable culture aligned with strategy. Both would be defined explicitly in regards to enabling technologies designed with constituent users (e.g., employees) in mind.
Regarding the path forward, clarity on approach – the “how” – could help build consensus to act. The primary difference between organizational change of the past and of today is in the change “levers.” Traditional change addressed structure, process, job design, and skills. Digital has affected this in several ways. First, structure is less critical generally. Staff managers and structured processes are less central to work planning because the team concept has emerged as a new focus of work design. Skills are still critical – however, the philosophy of who owns an employee’s development and learning is shifting as companies expect employees to own their careers and adapt quickly to changing business conditions.
So, what enables organizational capability in the digital age? We believe that work practices and culture are the primary levers today. Work practices represent the tangible, observable work at the intersection of formal work design and actual employee behaviors. Work practices can be evaluated, designed, and supported in action. This is where, for example, effective customer interactions occur – not through a static process flow chart or call script but through thoughtful human behaviors occurring within the context of good work design. This is where work analysis should be applied in order to identify change opportunities and to design new “ways of work.”
Or course, organizational culture sits behind this dynamic as a critical “glue,” providing an implicit reservoir of guidance for all sorts of situations and driving alignment in employee behaviors as the company deals with continuous, disruptive change.
Together these factors, when intentionally designed, serve as the drivers of the new digital organization. This is what is truly meant by “digital-first organizations” – where digital technology and digital behaviors are front and center in creating and executing the new work design.
Mary, an HR executive, sits in her office, trying to plan her day. She asks her assistant, Harold, “Did I receive a response from Marty Burns on the new leave policies?”
“Yes,” he replies. “Would you like me to read it you?”
“Yes, please,” she answers.
Harold reads the message to her – it’s a thoughtful response that she wants to follow-up on. “Schedule a meeting with Marty for 3pm today, please,” she says.
“Ok,” Harold replies.
Mary then asks Harold a few more questions about her upcoming appointments, and he reminds her that she has a meeting with one of her colleagues in fifteen minutes. She stands to leave, but before she does she asks Harold to request an Uber to take her to the airport that evening.
As Mary exits her office, Harold turns off the light and sits quietly in the dark, dutifully waiting for her return.
Harold is a digital assistant. If this scene seems futuristic, it’s worth noting that many of the tasks Mary asked Harold to carry out for her are actions that are readily handled by consumer devices such as Amazon’s Echo or Apple’s digital assistant, Siri. Bringing consumer, voice-driven interfaces inside the enterprise is part of a broader transformation which will redefine how employees interact with systems and data, and change how they get work done.
People are becoming increasingly comfortable with interacting with devices in a conversational way. As we have seen, consumer trends of today often become the enterprise trends of tomorrow. Voice-activated devices like the Amazon Echo give consumers ready access to all sorts of timely information, such as weather reports, online purchase tracking, and daily news briefings. Many have discovered the efficacy of using their voices to search for information, with a recent study showing that 43% of users reported that they felt as if voice search was quicker than using an app or website. With the adoption of this technology rapidly on the rise, forward-looking executives are beginning to think about how this new way of accessing information has the potential to drive productivity inside the enterprise.
Alexa, do I have any expenses to approve?As consumers have discovered, many frequent or daily tasks become far simpler when untethered from a keyboard. Inside the enterprise, we envision a not-too-distant future in which managers can ask questions such as “Is anyone on my team on vacation today?” or “Do I have any expenses to approve?” and get immediate access to important, actionable information. Executives will discover the benefits of having a digital assistant with an infallible memory, who can take a memo, schedule meetings, and provide helpful reminders, leaving the mundane tasks to the machines and letting their human assistants focus on high quality interactions that require a more personal touch.
Managers and executives aren’t the only ones who could derive benefits from voice interfaces, though. One can imagine that all employees would benefit from being able to simply ask, “How much vacation time do I have left?” or “When is my next meeting?” Yesterday’s dashboards become tomorrow’s daily briefings, with key data just a question away.
The voice-driven interface is just one of the ways the digital employee experience will evolve in the near term. Innovative business solutions will soon begin to transcend the limitations of the traditional desktop by embracing enabling technologies that will transform the way people work, and ultimately, transform the business itself.
Digital transformation is fueling many kinds of evolutionary and revolutionary impacts to the digital Employee Experience within the Enterprise. Advanced technology capabilities in Artificial Intelligence, such as machine learning and natural language processing are increasingly being applied to the consumer space, and are now emerging as ripe for enabling smarter, more engaging experiences for enterprise employees.
Natural language processing (NLP) and chatbot capabilities are currently used in the consumer space for a variety of interactions ranging from answering customer questions to servicing requests for action and even ordering products.
Employee needs can be serviced in similar ways that offer an opportunity to re-imagine how employees engage with enterprise resources, and to leverage more modern interactions that are becoming increasingly familiar and expected. By taking a look at how NLP and chatbots function, and could be applied to enterprise contexts, we hope to inspire creative thinking on propelling digital employee experiences into new paradigms.
Natural language processing allows spoken or written phrases to be analyzed by computers in order to determine the intent of the user. An intent can indicate the subject of the request or an action the user wants to take. The entities represent any pieces of information that provide proper context for a request or additional information required to complete an action.
In the example below, a manager has made a request for the amount of sick time used by a team member.
This phrase is run through a natural language processor to determine the intent and related entities. From this example, we can see that the intent has been identified in the context of the request along with two entities that help to focus the query to a specific user and with a specific conversion of time.
In order to determine intents and entities, the natural language processing platform must be provided a set of sample phrases that are mapped to a specific intent. This is a task that is performed by an administrator that is specifically trained to manage this process. As the administrator provides sample phrases for an intent they identify the entities that are present in the phrase.
Once an acceptable number of phrases have been provided and processed, the administrator initiates a training process within the natural language processing platform. This uses machine learning techniques to identify similar phrases for each intent.
As new phrases are provided by end users, the administrator can review them to ensure the natural processing platform is correctly identifying intents and entities. Corrective action is taken during this cycle to improve the accuracy of the platform.
Allowing users to have natural conversations with a system opens up new possibilities for accessing content and services. Users can make direct inquiries in a natural way rather than rely on traditional navigational or search capabilities.
A chatbot is a technology that allows users to have natural conversations to access content and services. Chatbots typically take the form of a chat client, leveraging natural language processing to conduct a conversation with the user. Chatbots control conversation flow based on the context of the user’s requests and respond with natural language phrases to provide direct answers, request additional information or recommend actions that can be taken.
The diagram below provides a high level description of how a chat client could be used to leverage natural language processing to assist with access to content or perform data queries.
The use of natural conversation will give users access to content and data in a manner that conforms to their needs. Users will no longer have to rely purely on search or navigation to find the content that is relevant to them. Enterprise services can be leveraged and made contextual for employees within the framework for a chatbot that maps those services to intents that NLP can extract.
An unprecedented range of machine learning and natural language processing capabilities exist today that can enable this type of smart experience within enterprise applications. This paradigm for fronting enterprise services with natural conversation has tremendous potential for revolutionizing the digital Employee Experience.
The bring-your-own device (BYOD) movement demonstrated how consumer experiences and expectations can change the enterprise ecosystem as well as the culture of a workplace. It brought an array of benefits to both the employee and company while presenting obstacles and ongoing challenges for IT organizations.
Security and data management policies are just some of the considerations that have to be accounted for in order for BYOD to become a reality for the enterprise down to the end user. Yet, if there is one thing that is true, technology is evolving at a greater pace than ever before. With that, BYOD can be looked at as the starting pistol shot signaling more things to come.
As devices improve with new capabilities and functionality, they grow closer to interpreting user interactions. They now anticipate behavioral actions through inputs and data collection:
Little by little, the devices we carry are inching towards a level of intimacy that will soon transform them more deeply into personal assistants. They will know more about us on a behavioral level and be able to anticipate the things we may need, the information we seek and the communications we have.
In addition, the form factor is rapidly changing. BYOD, for the most part, concentrated on smartphones and tablets. Now, technology has advanced to a variety of smaller devices such as wearables. (Think: fitness trackers, watches and smart glasses).
Wearables accentuate the intimate relationship that people have with their personal devices.
In short, yes, but like BYOD it will require organizations to plan and consider how to best use this technology to benefit both the company and the employee. At a high level, wearables can help create experiences in the workplace that are engaging and interactive while being productive.
With the potential to improve communication, productivity and collaboration in the workplace, enterprises must consider how to accommodate for wearable technologies beyond device provisioning. They must look to find ways in which they can tap into that intimate relationship and enrich the employee experience.
In doing so, they will ultimately excite, engage and retain their workforce. At Logical Design Solutions, we are constantly evaluating and innovating with emerging technologies like wearables for enterprise use.
Technology awareness and responsiveness to dynamic ideas of people in environments, or ambient computing, will change the way functionality, search capabilities and user experiences all get enhanced in future enterprise solutions.
The use of technologies like those found in Amazon Echo, Apple’s Siri, and in Microsoft’s Cortana will streamline certain enterprise functions while providing new and exciting experiences to business consumers.
The ability to connect people with business information, decision support data, and a range of tools and resources via simple voice commands is just the start of capabilities that lie ahead. In addition to the elegant user experience possibilities, an individual’s voice contains unique pattern identifiers that can provide systems with another layer of authentication and ultimately enhanced security.
Even more exciting, ambient computing brings together a range of disparate resources, is always-on and constantly learning about the environment and the people in it through interactions. It has a contextual awareness that can recognize a situation and then respond with relevant information.
For example, as a business user I may have access to a repository of many thousands of resources that I typically search within. If my traditional use of search is such that I have to filter and refine the terms I use, search remains an arduous process.
Yet, a smarter, integrated solution that considers information from my profile, my recent inquiry history and other learned variables, such as time of year relative to key business events, could yield results more meaningful to me. In the future enterprise ecosystem, you could envision people managers using solutions like these to monitor and manage their entire talent management pipeline!
In terms of experience design, nothing could be more elegant and simplistic than using one action to cull what’s relevant from vast amounts of information using only your voice. These possibilities will delight enterprise consumers with value, utility and a friction free experience across channels and devices.
The Internet of Things (IoT), for the most part, has already created various methods and means by which data can be collected and exchanged. As innovation continues, the consumer market will likely lead with progressive solutions in the area of ambient computing that will naturally extend to the enterprise.
The enterprise will be able to use best-of-breed solutions and apply them to create more useful and more seamless user experiences for their constituents.
Organizations can take cues now by following the growth of ambient computing within the in-home, consumer market where much of the initial progress is taking shape. The “connected-home” is the beginning of a small scale model for larger future state enterprise environments. All of the elements are there for consideration including network, device, security, profile and content management.
Using this line of sight can enable organizations to gauge which aspects of ambient computing will be most beneficial to employees in both the workplace and at home, providing them with an enhanced and seamless user experience.
At LDS, we’re always looking for ways to capitalize on modern technology disruptors, like ambient computing, to design relevant digital business experiences that create competitive advantage!
There are so many interesting things you could say about data in enterprise solutions; big data, operational data, stewardship, security, integration, design, semantics, modeling, governance, architecture… the list goes on and on…
Let’s talk for a minute about HR (who’s a big enterprise stakeholder in what we’ll call “people data”), and how we regularly see HR data leveraged in our solutions to deliver real value to the business and to business consumers…
We like to think about people data in some broad categories:
So how do we effectively leverage and capitalize on these classes of data in enterprise solutions?
One way you might think about it is to provide access to data centrally, and let people reference and report on these in different contexts of the employee lifecycle. In a model like this, a user needs to connect data to the context in which they are coming from, and may need to reason about relevant data in that context.
Although the idea of centralized user data in location sounds attractive from an engineering perspective, the burden on the user to rationalize what set of data to reference, or update under what conditions quickly becomes daunting – and it doesn’t really match the online behavior of most business consumers, most of the time. Some data, which may have relevancy across many different contexts, may be appropriate to provide centrally.
Another approach is to provide just the relevant set of data based on specific user situations / process contexts as the user is experiencing the online solution. Not only is this kind of distributed data in context simplifying the amount of rationalization the user has to do, these data could go beyond just displaying relevant data but also recommend specific actions that the user needs to take or consider in relation to the context. In this way we can influence behaviors! What power!
So what should business and data architects consider as they contemplate approaches like this?
Data Availability & Quality: In diverse and global organizations, data in each of the above mentioned categories may be highly fragmented due to variability in technology, processes, and local regulations. Enterprise HR solutions need to address data availability, consistency, quality and reliability and the likely coverage of these data to user populations before bringing select candidates for user consumption.
Entitlements: Complex rules may also drive who can see these data derived based on HR service delivery models (i.e., how clearly responsibilities for client organizations are defined) for HR access to these data, and how organizational responsibilities are delegated to people managers. These need to be well understood to appropriately factor related complexity to enabling these data to these important constituents (i.e., HR and Managers).
IT Strategy: Consider the larger HR ecosystem to validate that the data represented in the primary online channel is aligned and consistent with other properties in the ecosystem where a user may navigate to as a result of data displayed.
Readiness: Provide due considerations for technology readiness, capability and reliability to organize these complex data landscapes, enforce security and governance, to ensure that your business solution can consistently deliver a single source of truth, in real-time.
In diverse and global organizations, data in each of the above mentioned categories may be highly fragmented due to variability in technology, processes, and local regulations. Enterprise HR solutions need to address data availability, consistency, quality and reliability and the likely coverage of these data to user population before bringing selecting candidates for user consumption.
Complex rules may also drive who can see these data derived based on HR service delivery organization (i.e., how clearly responsibilities for client organizations are defined) for HR access to these data, and how organizational responsibilities are delegated to people managers. These need to be well understood to appropriately factor related complexity to enabling these data to these important constituents (i.e., HR and Managers).
Consider the larger HR ecosystem to validate that the data represented in the primary online channel is aligned and consistent with other properties in the ecosystem where a user may navigate to as a result of data displayed. Provide due considerations for technology readiness, capability and reliability to organize these complex data landscape, enforce security and governance, to ensure that your business solution can consistently deliver a single source of truth, in real-time.
So, as you can see, data is an important and complex idea in online enterprise solutions. There are important nested decisions to solve the use of data to achieve business goals, related technology, and data governance. At LDS, we’re accustomed to working through this problem space to unlock new value in the experiences we imagine, design and realize.
At Logical Design Solutions, we pride ourselves on designing intuitive user experiences that help our clients achieve their business objectives. When a design is truly effective, it will often hide the inherent complexity that tends to exist inside the enterprise ecosystem.
But to a software engineer, understanding that complexity and being able to harness the power of those complex systems can be one of the most challenging and rewarding parts of the role. At LDS, our engineers work closely with user experience experts, visual designers, and content analysts to take their innovative designs and make them a reality.
Engineers are involved early in the design process at LDS, bringing their technical insights and applying critical thinking to help refine and shape the solution. Through this iterative process, our teams produce logically complete solution designs that satisfy business requirements while caring for necessary ideas of budget, timeline, and technical feasibility.
The front-end, of course, is only one piece of the puzzle. LDS engineers also design and develop robust application architectures to provide all of the services and sub-systems that make the solution work. These systems must care for details such as personalization, security, content management, and other foundational ideas of the solution. Furthermore, they often enable complex integrations with third party applications, cloud services, and other systems in the enterprise ecosystem.
Our engineers implement these solutions across a wide range of platforms and technologies. While they possess deep knowledge and experience on platforms such as Microsoft SharePoint and IBM WebSphere, we expect our consultants to be software engineers first, and product specialists second. We put primacy on elegant engineering, thoughtful problem solving, and rational decision making.
Implementing a solution isn’t always just writing code, of course. Our engineers must be equally comfortable writing custom software and configuring off-the-shelf products to achieve solutions that appropriately care for the “build vs. buy” equation.
Engineers, above all else, enjoy building things. Specifically, we enjoy building things that are useful to people. At LDS, we are challenged every day to solve new problems and implement complex solutions. These solutions solve real business problems for some of the biggest companies in the world. The software we write is used by thousands of people, globally, each day. It’s a challenging, deeply rewarding experience, and one that affords regular opportunities for learning.
Are you an experienced software engineer who…
If so, please take a moment to review the career opportunities on our site and submit your resume today.