Tag: digital transformation

Design Thinking Series, Part 1: Why Digital Transformation Projects Fail

Posted by on July 09, 2019

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…if you can’t get the sum of the parts to be greater than the cost you’re going to fail and I think a large part of that 84 percent that fail it’s because they’re not prepared to change behavior. They think they can have strategy and technology and it just doesn’t get them there fast enough or in a good enough way.

— Michael Gale
Forbes Magazine,
“Why 84% Of Companies Fail At Digital Transformation”

Digital Transformation is growing is priority for most businesses, small and large. Virtually every company in the Forbes Global 2000 company list is on some sort of journey towards evolving their workplace in response to changes  in the way people interact with technology. While a few of these companies are reaping the rewards of embracing a growth mindset towards technology, many are struggling to make it happen or simply not seeing any benefits.

According to Michael Gale, a digital transformation expert, “Some are getting it right and others struggle.  Basically, one in eight got it right and then there were ranges of failure where more than 50 percent just didn’t go right at all.”

Part of the problem, though, is that it takes more than shoe-horning new technology onto old models and processes to create a successful digital transition. To find the right solution requires companies to dig deep into not just the “how” but the “why” they do things. Rather than trying to find the answers, businesses need to make sure they are asking the right questions first. That’s where Design Thinking comes in.

Why Digital Transformations Flounder or Fail

A staggering 84% of digital transformation projects fail, according to Michael Glaze who has been studying the topic for several years. According to a HarveyNash/KPMG survey, only 18% of CIOs said that their Digital Transformations were “very effective.” A less than 1 in 5 success rate would not lead to much enthusiasm or confidence if you are considering such a project.SOURCE: Harvey Nash/KPMG CIO Survey 2017, Navigating Uncertainty, Pg. 26<br /><br /><br /><br />

SOURCE: Harvey Nash/KPMG CIO Survey 2017, Navigating Uncertainty, Pg. 26

The exact cause of each failure is unique, but the reasons at the heart of all of these failures is lack of awareness of the challenges to be faced and the inability to shift focus as new challenges present themselves.This happens because many organizations still not only use, but think in terms of a long term waterfall methodology, where solutions are created early on and expected to be executed despite changing realities during the design and development.

This not only invariably leads to the dreaded scope creep, where timelines and budgets are crushed, it also means that as new research, and new information becomes available, it is often too late to integrate that knowledge into the final solution.

How Projects Succeed

Although there are a lot of factors that can cause projects as large and complicated as a Digital Transformation initiative to fail, there are several best practices we can bring to bear. These do not necessarily remove the problems, but will help to recognize and recover from them more quickly.

  1. Clearly define audience needs and what success will look like for them. It’s easy to believe that you understand your target audience and what they are looking for. You don’t. Even if you are a part of that target audience, you are likely only one of many. It’s important to get out and talk to them whenever and wherever they will be using the solutions you are trying to create.

  2. Clearly define what success looks like to the business and what is the value. All too often directions are given from high levels in the company without a full understanding of what is being asked. Try to work with the decision makers to understand what they think the optimal outcome for the project is and what value they hope to derive, and educate them on the realities of what they are asking for.

  3. Clearly define the technologies to be deployed. It is important to not let the technology dictate solutions, however, it is a reality that it does direct what is possible. It is vital that all parties including designers) understand the limitations and strengths of whatever technologies will be used.

  4. Make audience involvement and testing a part of the process, not an afterthought. Although this might sound like a rehashing  of tip #1, we often forget about the people we’re actually creating for. It’s important to constantly get reality checks from your audience to make sure you are headed in the right direction.

  5. Design & Development in Steps. As mentioned, waterfall just doesn’t cut it anymore. Instead, both development and design must create in iterative steps, allowing them to bring in new insights and information to the solutions as they work.

This last tip is crucial. For developers the iterative step-by-step method is the Agile process using development sprints. Designers have, by and large, been reluctant to enter into a sprint based process, although iteration is a cornerstone of design.

Over the last few years designers have been increasingly embracing the concept of Design Thinking along with the even more recent concept of design sprints. Although still gaining support, success stories of a proper Design Thinking approach are winning converts.

Enter Design Thinking

Design thinking, to be reductively simple, means “thinking like a designer” in order to develop solutions. According to Thomas Lockwood in his introduction to Design Thinking: Integrating Innovation, Customer Experience, and Brand Value, the value in design thinking is that: “By thinking like designers—being able to see the details as well as zoom out to the big picture—we can really add value by challenging the status quo.”

Design Thinking reverses the way many people approach problem solving, allowing them to discover more innovative solutions than they might normally come to. Rather than starting with requirements and features and finding a solution, we start with the user needs and desired outcome (the big picture) and work to find the best way(s) to make that happen by asking the right questions, the first of which is “Is it worth it?”.

This approach  brings together what is desirable from the audience’s (user, customer, partner, employee, etc.)  point of view with what is viable for the business and technologically feasible. It also means engaging people who aren’t trained to design,  but who have to live with the results of the designs, to use creative tools to innovate solutions for a wide range of challenges.

Lockwood lists three primary tenets for design thinking in his introduction:

  1. Develop a deep understanding of the audience based on fieldwork research.

  2. Collaborate with the audience through the formation of multidisciplinary teams.

  3. Accelerate learning through visualization, hands-on experimentalism, and creating quick prototypes, which are made as simple as possible in order to get usable feedback.

However, in our experience designing digital products, we have found that — while excellent for thinking about visual and some interactive issues — current design thinking methodologies leave out how that design fits into the longer term narrative for the audience.  So we add a fourth point:

  1. Follow the rhythm and flow of the audience and how their needs and goals change both in context and over time.

Ok, enough theory, let’s talk practical application. To apply the design thinking process, we make use of two main activities: Design Thinking Workshops and Design Sprints.

Design Thinking Workshops

The Design Thinking workshop is used to kick-off the design phase of a project. This is a process of applying human centered design principles, focusing on deconstructing the problem and then reconstructing it for the solution. To be effective, this means embracing a Lean UX philosophy and creating functional prototypes to quickly iterate the best solutions within the time, budget, and technical limitations.

Design Sprints

Design sprints — developed by Google Ventures (gv.com) — have been applied to help companies from start-ups to Fortune 500s to quickly and accurately prototype and test user experience concepts which can then be developed into final working products.

A single sprint is not meant to design an entire site, section, or even page, but instead to examine the user’s process and how it can be improved within the system.

Using Design Sprints allows iterative improvements without locking into a set roadmap that might need to change in order to meet shifting conditions and priorities. Instead, we define the goal for that month’s design sprint, pulling from a backlog of requests and work to resolve that particular task. As new requests come in, they can be added to the backlog, and then considered for the next sprint, allowing ongoing refinements.

How Design Thinking can Accelerate a Digital Transformation Initiative

The Design Thinking process is a tool that can be applied to any project to address many of the reasons Digital Transformation projects fail.

  1. Audience involvement is integral to developing ideas that are turned into  features. Not only is there regular testing of the product with the people who will be using it, they are also invited in to help brainstorm possible solutions. This ensures that their needs and expected outcomes are met.

  2. Business and tech needs are brought in early. Confirming that the product is both viable from a business standpoint and feasible from a technology  standpoint are constant considerations during the process.

  3. It is an iterative process that can work in close conjunction with an Agile process. Unlike in a waterfall methodology, foundational work on the design is done early, but full design implementations are done in sprints, with feedback from development to constantly refine and improve solutions.

Design thinking is not a magic bullet that can fix everything or prevent all issues from arising. What it does provide, however, is a methodology to better adjust and react to changing priorities and realities during product development. This ensures that whatever challenges you face, you are better able to handle them without derailing the entire project.

Contact Rivet Logic to learn more about how we can help you with your digital transformation initiatives!

Machine Learning is State-of-the-Art AI, and It Can Help Enhance the Customer Experience

Posted by on October 05, 2017

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Is artificial intelligence the same as machine learning? Machine learning is really a subset of artificial intelligence, and a more precise way to view it is that it is state-of-the-art AI. Machine learning is a “current application of AI” and is centered around the notion that “we should…give machines access to data and let them learn for themselves.” There is no limit to that data (or Big Data).  The challenge is harnessing it for useful purposes.

In his Forbes Magazine piece, contributor Bernard Marr, describes AI as the “broader concept of machines being able to carry out tasks in a way we would consider ‘smart.’” So, AI is any technique that allows computers to imitate human intelligence through logic, “if-then” rules, decisions trees and its crucial component, machine learning.  Machine learning, as an application of AI, employs abstruse (i.e., difficult to understand) statistical techniques, which improve machine performance through exposure to Big Data.

AI has broad applications…

Companies around the world use AI in information technology, marketing, finance and accounting, and customer service. According to  a Harvard Business Review article, IT garners the lion’s share of popularity in AI activities, ranging in applications that detect and deflect security intrusions, to automating production management work. Beyond security and industry, AI has broad applications in improving customer experiences with automatic ticketing, voice- and face-activated chat bots, and much more.

Machine learning is data analysis on steroids…

AI’s subset, machine learning, automates its own model building. Programmers design and use algorithms that are iterative, in that the models learn by repeated exposure to data. As the models encounter new data, they adapt and learn from previous computations. The repeatable decisions and results are based on experience, and the learning grows exponentially.

The return of machine learning

Having experienced somewhat of a slump in popularity, AI and machine learning have, according to one software industry commentator, Jnan Dash, seen “a sudden rise” in their deployment. Dash points to an acceleration in AI/machine learning technology and a market value jump “from $8B this year to $47B by 2020.”

Machine learning, according to one Baidu scientist will be the “new electricity,” which will transform technology. In other words, AI and machine learning will be to our future economy what electricity was to 20th century industry.

The big players are pushing AI and machine learning. Apple, Google, IBM, Microsoft and social media giants Facebook and Twitter are accelerating promoting machine learning. One Google spokesman, for example, recognizes machine learning as “a core transformative way in which we are rethinking everything we are doing.”

How Machine learning has transformed General Electric…

A striking example of how AI and machine learning are transforming one of the oldest American industries, General Electric, is highlighted in this Forbes piece. Fueled by the power of Big Data, GE has leveraged AI and machine learning in a remarkable—and ongoing—migration from an industrial, consumer products, and financial services firm “to a ‘digital industrial’ company” focusing on the “Industrial Internet.” As a result, GE realized $7 billion in software sales in 2016.

GE cashed in on data analytics and AI “to make sense of the massive volumes of Big Data” captured by its own industrial devices.  Their insights on how the “Internet of Things” and machine connectivity were only the first steps in digital transformation led them to the realization that “making machines smarter required embedding AI into the machines and devices.”

After acquiring the necessary start-up expertise, GE figured out the best ways to collect all that data, analyze it, and generate the insights to make equipment run more efficiently. That, in turn, optimized every operation from supply chain to consumers.

5 ways machine learning can also enhance the customer experience…

Machine learning can integrate business data to achieve big savings and efficiency to enhance customer experiences, by:

  1. Reading a customer’s note and figure out whether the note is a complaint or a compliment
  2. Aggregating the customer’s personal and census information to predict buying preferences
  3. Evaluating a customer’s online shopping history or social media participation and place a new product offering in an email, webpage visit, or social media activity
  4. Intuitively segmenting customers through mass customer data gathering, grouping, and targeting ads for each customer segment
  5. Automating customer contact points with voice- or face-activated “chat bots”

How Rivet Logic can make you future-ready and customer friendly

Your business may be nowhere near the size of General Electric. You do, however, have a level playing field when it comes to leveraging Big Data and machine learning products to a winning strategy. What we do is help you plan that strategy by:

  • Aligning your business goals with technology—What are the sources of your own data and how can they harness the power of NoSQL databases, for example?
  • Designing your user experience—What do you need? A custom user interface, or a mobile app with intuitively simple user interfaces?

We can do that and much more. Contact us and we’ll help make your business future-ready to collect, harvest, and leverage all the great things you are doing now.

Approaching the C-Suite Regarding Digital Transformation

Posted by on September 06, 2017

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Even though digital transformation may be the next necessary step for a business, it can often be difficult to get the entire c-suite on board. It’s easy to understand why: on the surface, a digital transformation can appear to be a business disruption. It can seem both costly and unnecessary to those who aren’t aware of the technology that is now available to them… and it can be a difficult pitch to a board of investors. Nevertheless, digital transformation is absolutely critical to a thriving enterprise.

Understanding the Major Reservations Regarding Digital Transformation

Though it can seem as though the c-suite is being stubborn about transitioning to new technology, it’s understandable why a complete transformation of digital infrastructure may cause them to hesitate. There are generally a few major reservations regarding digital transformation:

  • Cost. Any investment in software is likely to be an unscheduled expense for the business. Just a decade or two ago, digital transformation could be incredibly costly, necessitating new hardware, licenses, IT training, and more. Most of the c-suite will still remember the days when a digital transformation meant dramatically revamping the entirety of the technology of an office, from telephones to personal computers.
  • Disruption. Likewise, digital transformation has historically been the source of significant disruption. Changing over both a hardware and software infrastructure leads to confusion and a loss of productivity, which can lasts anywhere from days to months. It’s the old adage: if it ain’t broke, don’t fix it. If the c-suite doesn’t see problems with current operations, they are going to be very hesitant to change anything.
  • Productivity. Employees aren’t the only ones hesitant to train in new technology. C-suite members themselves often don’t want to have to learn new technology; they may feel as though it’s going to damage their productivity and that they aren’t going to have access to the tools that they want to use.
  • Future needs. Finally, the c-suite may be hesitant to advance technology because they know that they’re going to have to advance technology again in the future; in other words, they may not want to upgrade now, because “we will just have to upgrade later.” Though there is a flaw in this logic, it can still present significant hesitation.

Of these concerns, the cost and potential disruption to the business are usually the primary concerns. Addressing these two major concerns is usually the best way to bring them on your side.

Addressing Concerns Related to Cost and Business Interruption

  • Break down the costs. New digital transformation technologies, such as cloud-based systems, are not as expensive to upgrade to as a physical infrastructure would be. When breaking down costs, additionally show the c-suite how much money this would save in the long run.
  • Focus on pain points. To show the value of a digital transformation, you should first show the problems that the business is currently facing and the areas in which technology could improve them. The c-suite needs to be shown that this upgrade is necessary and useful.
  • Demonstrate the solutions. Many of these solutions are easier and more intuitive than the c-suite could otherwise expect. Showing the c-suite the software solutions and familiarizing them will give them a better picture of the software’s benefits.
  • Create a roadmap for the future. The c-suite should be aware that many of these digital transformation solutions have their own future-proofing built-in, which means they will iteratively upgrade rather than having to engage in transformation again and again.

Getting the c-suite on board with digital transformation is simply a matter of showing and proving value. It is the c-suite’s responsibility to protect the business and its bottom line at all costs. What may seem like reluctance to evolve are simply well-intentioned reservations that need to be countered with facts, statistics, and a clear plan for change. Once these pieces fall into place, the c-suite will be able to see the true value of digital transformation.

Moving from Legacy Systems With Digital Transformation

Posted by on August 08, 2017

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Digital transformation. It may sound intimidating, but it’s vital to the operations of every organization. From small, single proprietorship businesses to large, sprawling enterprises, there comes a time when the organization is no longer being served by its technology. Digital transformation is a process through which organizations are able to upgrade and improve upon their technology, moving away from the legacy systems that may be holding them back.

The Danger and Inefficiency of Legacy Systems

  • Legacy systems are often unsupported. Businesses may find themselves continually using outdated legacy solutions because they simply don’t want to upgrade — but eventually the company producing these systems halts their support. It can become increasingly more difficult (and more expensive) to find technicians able to repair these systems.
  • Legacy systems aren’t compatible with new solutions. Though the temptation may be to upgrade a system piecemeal, this often does not work out because legacy systems are old enough that they cannot be easily integrated with newer systems. This holds the entirety of the infrastructure back.
  • Legacy systems are inherently less secure. Legacy systems were developed before new cyber security threats and are often not maintained in the wake of new ones. Because of this, legacy systems may be vulnerable to many types of attack.
  • Legacy systems are clunky and cumbersome. But perhaps one of the most compelling reasons to switch from a legacy system is that they tend to have a very negative user experience. Legacy systems may make all business processes take longer to complete.

The Benefits of Modern Software Solutions

Modern software solutions are efficient and scalable, both in terms of cloud-based solutions and new on-premise infrastructures. Organizations can invest in private clouds, public clouds, and entirely on-premise systems, which will adhere to modern security standards and be accessible and reliable. Compared to legacy software solutions, these modern systems are more focused on user experience and efficiency. They are able to take advantage of the resources offered by modern hardware, and consequently they are better able to handle the needs of a growing business. Modern software solutions are also better supported than their legacy counterparts, and finding individuals skilled in their use is far easier.

Transitioning from Licensed Solutions to Open Source Software

Licensed solutions need to be renewed every year — and they often go up in price based on the size of your business or the number of seats that you require. Open source software, on the other hand, is freely available for use without any fees… maintenance or otherwise. For businesses that want additional functionality and features, affordable enterprise editions are available, often for a low subscription based cost. When completing a digital transformation, there is often an emphasis on switching costly, proprietary licensed solutions over to open source platforms. Though there may be a cost associated with enterprise editions, it’s far less than proprietary software.

In addition to the cost, there are a number of benefits that open source software provides:

  • An extensive and well-supported code base. Open source software is often associated with large communities and dedicated developers, all working together to improve upon the system. Not only will the system be robust and well-designed, but it will also have continual support. Comparatively, many licensed solutions will drop support for their older products in just a few years.
  • Easily customized solutions. Open source software will often have modules and extensions designed to customize their suites to your needs — and even those that do not have modules and extensions can be easily customized by a talented programmer, as the code is available. Proprietary solutions may have APIs or nothing at all, which means that a business cannot acquire a customized solution unless they purchase it directly from the company at a high cost.
  • Better security. Open source software is frequently updated by a large number of contributors, which means that security issues are caught and patched very quickly. Many security flaws within a system are introduced through third-party solutions. For organizations that rely upon their technology, security, and privacy, open source software can be a more reliable method of reducing risk.

And, of course, cost is a major factor. By reducing the cost of your system, you can create a system that is more scalable — and you can devote the budget that would otherwise be allocated towards licensing to other areas of your IT budget.

Digital transformation is a way to improve all of your organizational processes with a single structured transition. Through digital transformation, your organization will be able to leverage vastly superior technologies, while also reducing costs and administrative overhead.