Portfolio management plays a critical role in R&D management, as it structures a strategic process that allows management and R&D to make joint decisions that impact the range of R&D projects in the development funnel. The pooling of insights drives better decisions on the allocation of scarce technical resources based on the needs of the business and its capabilities. Portfolio management creates a dynamic capability to react purposefully to changes in the market, whether strategic, technological, or competitive. This requires clearly articulated projects that can link back to corporate strategy.

As companies evolve through the stages of increasing agility, the work of HR changes as well. At each stage, there are new priorities and new hurdles that should be both expected and managed.

In this webinar, Cutter Consortium Senior Consultant Katia Passerini leads a discussion on the role of disruptive technology and how the process of innovation can drastically differ from what companies consider to be good business practices, as well as from what individuals are comfortable with.

Both the industrial and computer revolutions created a great deal of contemporary concern about massive unemployment, but these concerns never materialized beyond a few initial rough spots. Will the AI revolution prove equally problem-free? Probably not. Dangers lie ahead and will test the strength of our institutions as well as our technologists. The possibly massive job loss is the most tangible consequence; it would affect the greatest number of people. Smart robots keep replacing factory and warehouse workers and are showing up in service industries (e.g., self-checkout in supermarkets). AI’s machine learning and algorithms are industrializing much higher-skilled “artisanal” activity (e.g., interpreting x-rays, once thought invulnerable to automation). Nobody has good answers, but ideas like those explored in this Advisor are taking shape.

Many technologies exist today that have the potential to change the manner in which we get work done. Currently, the software developer job is heavily labor-intensive. Yes, we use software tools to perform many of the repetitive tasks; however, for the most part, the programming job is performed by highly talented individuals who specify, design, code, and test complex pieces of code and make them work. We have attempted to automate such tasks, but we can best characterize current efforts as assistance (helping workers by providing guidance and information) rather than automation (replacing humans with machines). In this Advisor, we identify 20 technologies that have the potential to alter this picture in both the near and long term. Some present opportunities, while others will disrupt our environments. And some will fall on both sides of that equation.

As we are making improvements in human-computer interfaces, we are subtly nudged into realizing that these interfaces are there only because the two worlds — human and computer — exist separately. Computers do what computers do, and humans do what humans do. Yes, computing has bled into the interface between the two, making the line in between a bit easier to traverse. And yes, we will continue to see improvements in this area as we move forward. However, none of these “advances” has accomplished any fundamental change in the division of roles and responsibilities across man and machine; they have not shifted the line between them. Arguably, what we have done over the past couple of decades is merely spread computing’s ability to automate specifiable rules across larger swaths of people. It may not be helpful to think of computer-based systems as tools — as human augmentation — anymore. We may need to rethink how we think about the computing landscape, and consider rejigging our tools of thinking, notably architecture. This Advisor suggests stretching in that direction so that we are positioned more effectively to meet a qualitatively different future as it charges rapidly toward, and at us.

Robotic process automation (RPA) has emerged as a popular technique to automate routine and repetitive human-system interactions across functional domains such as finance, marketing, human resources (HR), and other transaction-processing areas. Adopting such intelligent automation techniques allows businesses to enable efficiencies without major system transformations. Business leaders may find it compelling to invest in RPA tools and resources but should be aware of the foundational work required before rolling out the initial robots. This Advisor surveys the RPA vendor landscape, highlighting intelligent automation adoption across industries with a few user stories.

The ever-increasing pace of technology development and the emerging requirements for new cross-disciplinary competencies, especially in converging industries, place increasing demands on resource and competence management in R&D. If companies fail to develop, or target the wrong areas, consequences can be significant — and it can be difficult to recover. In this Executive Update, we examine a recent survey of large organizations worldwide on R&D best practices that shows how some leading companies are rising to the R&D challenge by developing resilience in their resourcing plans to avoid bottle­necks, taking a long-term view on required future competencies, and putting plans in place to develop competencies, often with external partners.

An organization seeking to become Agile should look to have a preponderance of generalizing specialists on their teams. There is, of course, room for some pure specialists, but too often businesses seek to hire a Python or Linux or Docker guru, when what they really need is someone “good enough” at one of those specialties but who also has broader technological and business understandings. Certainly, hiring a generalizing specialist may have some short-term downside in terms of cranking out the next couple of specialized projects, but most often that cost will be repaid several times over because it will create more cohesive and Agile teams in the long run.

Drones are in the ascent stage of the technology lifecycle — climbing out of the bleeding edge firmly into the cutting edge — and today’s potential for enterprise use of drones is unprecedented. Comparison with the path to maturity of the automobile is an apt one, and UAS (unmanned aircraft systems) industry growth and technology adoption will likely be just as circuitous and full of surprises, frustrations, and rewards.

In this on-demand webinar, Cutter Consortium Senior Consultant Jon Ward, describes how an Agile team was able to cut time-to-market in half and reduce the cost to deliver by 60%. He addresses how AI could have been used to even further enhance the team's productivity, where AI might inhibit it, and he outlines where AI can be used to improve your productivity.

In this on-demand webinar, Cutter Consortium Senior Consultant Jon Ward, describes how an Agile team was able to cut time-to-market in half and reduce the cost to deliver by 60%. He addresses how AI could have been used to even further enhance the team's productivity, where AI might inhibit it, and he outlines where AI can be used to improve your productivity.

We believe existing organizational development approaches are not far-reaching or holistic enough when it comes to the scope of the issues they address. Most methods either focus on strengthening the scale/productivity dimension (often within the context of Lean models) or push the speed/creativity dimension (commonly referred to as the Agile model). However, choosing either the Lean or the Agile path does not provide the right mindset and tools to address the complexity and competitive challenges of most large organizations. Moreover, those frameworks that are ambidextrous are not operationally focused enough to enable day-to-day management and lack a link between strategy definition and organizational development. From our experience, these missing qualities are essential to making well-informed business decisions.

In this Executive Update, we look at a purpose-driven approach to innovation that large global companies can successfully apply.

We are increasingly hearing about the rise of the “Chief Customer Officer” (CCO), who has the position and the authority to ensure that the organization provides a unified and seamless customer journey/experience (CX) across all customer channels. But just how standard is the role of the CCO among organizations? According to preliminary findings from our ongoing CX management survey, current use of CCOs — or someone with an equivalent title formally charged with overseeing the adoption of CX practices into the organization — is relatively popular, with approximately 27% of the organizations we have surveyed indicating that they have made such an appointment.

In this webinar, you'll discover why your organization should use a business architecture and value delivery–based approach to digital strategy. And you'll learn why provisioning the platform based on next-generation application, information, security, and technology architectures is critical.

From the moment a work crew from STS Construction (STS) showed up at my house until the whole project was finished almost a year later, I witnessed and participated in some of the best Scrum I have seen. Even though STS had never heard of Scrum and would not have known what the term meant, the company had come up with a way of working that was Scrum. Not only was I impressed by the tactical scrum onsite, but when I learned how STS did its project management and scheduling, I was equally impressed by its strategic scrum working habits. This Executive Update discusses the primary Scrum patterns and practices I saw in STS’s work that helped make our home remodel a success. (Not a client? For a limited time, you can download your complimentary copy here.)

Synthetic data provides a privacy protective mechanism to broadly use and share data for secondary purposes. Using and sharing data for secondary purposes can facilitate innovative big data initiatives and partnerships to develop novel analytics solutions. This Executive Update provides an overview of the use cases for synthetic data, how to generate synthetic data, and some legal considerations associated with synthetic data’s use.

Nowadays, companies are struggling to deal with a more and more sophisticated customer. Online and offline touchpoints are generally unbound, failing to create the unique and continuous journey customers expect. Companies must embrace a new approach in order to give strategic relevance and a clear purpose to the digital marketing practice. As described in this Advisor, this approach is based on seven major activities grouped into three areas, which recur iteratively to achieve progressively more accuracy and commercial success.

Artificial Intelligence (AI) — is it hype, a new industrial dawn, or simply a means to increase leisure time? We are putting AI into nearly everything, including our refrigerators and other domestic appliances. So what about Agile teams — how should they use it? AI in project management tools is not new; indeed it has been a decade since global enterprise software company Planview introduced the optimization engine for capacity and demand. However, it is only now that this AI feature is becoming more widely used. This Advisor explores how organizations can use AI to increase the performance of Agile teams by supporting the product owner.

We are entering an era that will demand unheralded levels of creativity because companies will need to constantly innovate and reinvent themselves to succeed in their search for growth and margins. Some leading companies are rising to the occasion by launching time-limited ideation challenges for key strategic issues and then instituting a dedicated process to enrich and select winning ideas. To sup­port this initiative, senior leaders must devote a significant amount of time to ideation and be fully involved from start to finish in the ideation process. Innovation leaders must also prevent excessive “infant mortality” of radical ideas and ringfence resources to maintain a balanced R&D portfolio. 

Robotic process automation (RPA) has emerged as a popular technique to automate routine and repetitive human-system interactions across functional domains such as finance, marketing, human resources (HR), and other transaction-processing areas. Adopting such intelligent automation techniques allows businesses to enable efficiencies without major system transformations. Business leaders may find it compelling to invest in RPA tools and resources but should be aware of the foundational work required before rolling out the initial robots. This Advisor explores some of challenges facing organizations looking to adopt RPA.

In my years of implementing SPM across different teams and organizations, the notion of an object can be distressing. Unlike its sibling hierarchy, phases, the object concept is not well understood or even implemented much of anywhere in other project methodologies, setting aside enterprise architecture methodologies, which often model objects more extensively. IT people accept the idea of a project phase without question. When confronted with the notion of an object, however, the apparent simplicity of the definition of an object transitions quickly to difficulty upon further probing. 

We can characterize the fourth stage of automation, smart automation, by intelligence embedded across customer channels (stores, call centers, websites, etc.), processes, systems, and platforms. Smart automation builds on the previous stages and uses intelligent means to bring automation to all aspects of a business value chain, from customer experience (CX), worker experience, internal processes, and operations to partner collaboration, covering all types of systems. As we explore in this Advisor, however, it is important that smart automation design carefully consider the subtle interplay between humans and machines to understand the nuances of those activities humans are good at and those for which machines are efficient and reliable.

In this Executive Update, we take a closer look at the design thinking method and delve into the actual design framework that companies are adopting to advance their ability to digitally transform. We explore the principles of inspiration, ideation, and implementation, along with the benefits of a design mindset. We also break down some myths that have plagued design thinking in the past.