Business Transformation Requires Transformational Leaders

Connecting a platform with an existing company to a platform organization is beneficial for both established companies and insurtechs. Without pursuing that ave­nue, the insurtechs face the risk that their competitiveness may decline if others can copy their digital skills at low cost. Thus, connecting their platforms with the incumbent organizations that possess hard-to-copy capabilities guarantees the uniqueness and sustainability of their own business model. The disadvantages of established companies, in comparison to insurtechs, are the reason why tradi­tional companies need platforms. Platforms require changing the culture and business logic in a company from product to service dominance, making proc­esses in relevant areas real-time capable, opening the company to the reuse and integration of solutions and services from other actors, and replacing a hierarchical culture with modern, agile, team-oriented approaches that make optimal use of the internal and external workforce.

Here in Part II of this Executive Report series on the rise of cognitive computing, we dive into the commercial cognitive products, including cognitive development platforms, domain- and industry-specific cognitive platforms, and cognitive-powered solutions

Here in Part II of this Executive Report series on the rise of cognitive computing, we dive into the commercial cognitive products, including cognitive development platforms, domain- and industry-specific cognitive platforms, and cognitive-powered solutions

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.

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.

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.