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

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.

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. 

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. 

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. 

Innovation at its core relies on focused creative thinking, which allows organizations to respond successfully to situations that do not have easy answers or readily apparent solutions and drive results in a collaborative emergence of novelty and marketable value. This focus originates within teams staffed and equipped to apply their collective creativity and experience to business challenges, which fosters the opportunity to make enhanced real-time decisions that benefit both the enterprise and its stakeholders. As we explore in this Executive Update, it is the creative collaboration of organizational teams, in concert with end-user sentiment, that drives the most effective innovation.

This Executive Update asks whether teams can use AI to increase the performance of Agile teams. Data collection, analysis, prediction, and reporting tend to make up a large proportion of the AI capabilities used in the project and portfolio management disciplines. Most tools are not uniquely oriented toward Agile delivery; this Update will concentrate on the Agile dimension. (Not a client? For a limited time, you can download a complimentary copy of this article here.)

Many IT shops often manage dozens and hundreds of active projects. This project-planning work tends to be distributed well beyond a central project management office. There are only so many project managers in the world, and there are often too many project plans to create and manage. To help both our project managers and those in IT (or elsewhere) who operate as project managers without the deeper training project managers often have, we have drafted a rubric that make clear what we are looking for in a project and a project plan.

Most organizations simplify their implementation of methodologies. The quantity of knowledge in a given methodology is greater than its applied usefulness, so much of the methodology remains, probably very safely, as shelfware. In other more malignant cases where the leaders wish to see more rigor from their staff, the methodology can become overburdening. In statistical project management (SPM), we simplify the project management approach by eliminating many concepts that the dominant project management methodologies consider central. While I caution you to err to the side of adopting a lighter methodology rather than a thicker one, that choice is a local one and yours to make. The SPM ontology is presented in this Executive Update provides you with options.

Agile transformation often starts as a grassroots experiment of “doers” but cannot deliver the most valu­able results — increased business agility — without involving company management to face some bold deci­sions. We invite you to view the “Rubicon decisions” described in this Executive Update as generic milestones on an Agile transformation roadmap.

Here in Part XIII, the final Executive Update in Senior Consultant Curt Hall's series on artificial intelligence (AI) and machine learning in the enterprise, we focus on findings surrounding the hype around AI and the potential for the technology to lead to social and economic disruption.

Successful companies have achieved outstanding performance by incorporating Lean management at the center of their corporate transformations. At the same time, the potential of digital technologies to transform performance has become widely recognized. However, bringing together Lean and digital tends to bring about two conflicting scenarios: companies that realize a radical performance increase of up to 50% or more, or companies that become stuck in situations in which initiatives happen in silos, efforts lack coordination, and success is never achieved. This Executive Update offers guidance on trans­forming companies to digital Lean by developing their Lean capabilities and embedding technological building blocks into their value streams.

Here in Part XII of this ongoing series on artificial intelligence (AI) in the enterprise, we examine findings pertaining to the use cases that organizations in our study viewed as most viable for applying AI.

In Part VI of this Executive Update series, we take a look at “the procrastination metrics" of V5  and V8.

Our behavior style is based on other people’s perceptions of us, not on how we see ourselves. There is no good or bad style. We all, unconsciously, seek out others who have a style similar to our own, and we can all tell, again unconsciously, who has such a style and who doesn’t. Having the knowledge to predict the interaction problems we may encounter with other people provides us with a basis for improving the quality of our interactions. This improvement in our “situational awareness” gives us the ability to better control the outcomes of our interactions with others.

This Executive Update describes the Ambidextrous Organization Development Canvas and how it enables management teams to discuss organization development issues in a common language and make decisions on development aims and organization transformation priorities. (Not a Cutter member? For a limited time, you can download your complimentary copy here.)

Here in Part XI of this Executive Update series, we look at how responding organizations view the success of their AI application development efforts to date, including whether they are deriving any benefits from their deployed AI applications and whether such applications are, in fact, actually changing how their organizations operate. 

Though robotic process automation (RPA) implementations mimic humans and replace human effort, they cannot, as of yet, replace humans’ emotional ability. By freeing humans from repetitive tasks, RPA will allow humans to focus on better understanding customer needs in different situations and better connection with customers. Humans can then perform tasks that require uniquely human strengths like emotional intelligence and judgment, enabling better interaction with customers.

This Executive Update takes a closer look at being Agile when it comes to firmware. We begin with some tutorial information. Next, we discuss the firmware development process. Finally, we explore the issues typically encountered and identify ways some have taken to resolve them.

Milestones are just an independent, simple, one-level hierarchy that stands side by side with our object list. That said, when milestone commitments (estimated end dates) change — or when teams deliver work ahead of, or lagging behind, the milestone estimated end date — these all become important changes and outcomes that we need to monitor. Monitoring these changes gives us insight into the nature of project scope changes and the interaction between our project management team and IT governance. 

In this, the final Update of the series, we summarize the ideas we have discussed with the goal of leaving you, the business analyst, with a starting point for the application of Agile principles.

In this Executive Update, we focus our attention on the intersection of design thinking (as a method for understanding opportunities through a different lens) and digital transformation (the use of technology to radically improve performance or reach). In many cases, digital transformation is employed in an effort to create a competitive advantage, which in today’s business environment can at best be considered a transient advantage because sustaining anything for a long period of time is highly unlikely. 

In Part X, we examine survey findings pertaining to current AI application design and development trends and plans by organizations to utilize outside AI experts and to train employees in AI development. 

This continuation of my previous Executive Update series encompasses my experience with this method of project management beginning in 1992 and continuing with successive waves of improvements across five different organizations — two in the consulting business and three within university CIO offices. Here in Part IV, we look at metrics V3 and V4.