Our monthly innovation updates provide you with an overview of the most relevant insights, best practices & tools from the innovation cosmos.
According to a study by McKinsey, more than nine out of ten executives are unsatisfied with the innovation performance of their companies. If you belong to this group or if you are part of an innovation team, you should check whether you employ the right innovation governance model. You should check whether it is clear what needs to be delivered and how to organize your teams best to achieve superior innovation performance.
Defining sound innovation governance that clarifies the objectives, responsibilities, accountability, and coordination is crucial for high performance. A sound governance model trickles down corporate aspirations into expectations towards innovation teams and forms the paths for their activities.
There are four essential building blocks of innovation governance you should consider:
1. Objectives and key results
Formulating clear objectives and key results are the first building block of sound innovation governance. What contribution do you expect from your innovation team(s)? How much of your business growth should come from innovation activities over the next years? Is it ten percent or thirty percent in annual sales volume? Do you expect any contribution to savings based on better, more automated operations? If so, how much?
Setting aspiring targets for innovation teams is the first step to making them accountable and relevant to the business. If you institutionalize this general objective, your teams will add the other building blocks more or less effortlessly because any of their activities need to fuel the achievement of such goals and results.
2. Responsibilities and jobs to be done
Building the fundament with clear goals and expected key results is the cornerstone of your teams’ activities. If they know what they need to deliver, they can design their jobs accordingly. If you put them on the journey to grow ten percent outside your core business, they will need to design a path that scouts for external opportunities and, most probably, partnering firms to accelerate the ramp-up. In contrast, if the goal is to gain more from existing operations, the teams will work more closely together with your existing business functions. In any case, the form of responsibility follows the function or, better said, objectives. It is a cycle that needs to be closed.
3. Accountability and reports
Closing the cycle, of course, requires splitting the responsibilities among different co-workers and making each co-worker accountable for working against the general objective within their domain. Every co-worker needs to have their objectives and key results. And every co-worker needs to be accountable for pushing updates regularly on their achievements. You have to ask yourself, how do you steer everyone’s accountability? Do you ask for individual reports every week? Or do you allocate time in recurrent meetings to check in on progress, blockers, and achievements? No matter what format you use, you may want to close this cycle between objectives, jobs to be done, and regular reports.
4. Coordination and autonomy costs
Sound formulations of objectives, responsibilities, and accountability will already help you steer individual performance. However, the more individuals you employ, the more coordination between such individuals will be needed. Without any coordination, autonomy costs will rise tremendously. This refers to the costs arising from double work, misinformation, or free-riding behaviors. To reduce such costs, you need to invest in coordination and information tools. The larger the organization and the more diversified your activities, the less efficient will coordination formats such as meetings and written reports be. That’s where only employing professional innovation operating software (OS) reduces coordination costs between teams, regions, and departments.
Taken together, the key benefit of innovation governance is helping you close the cycle between objectives, responsibilities, accountability, and coordination. How good are you at closing the cycle? Download our Governance Framework template and start mapping your aspired innovation governance today!
How do you identify and empower innovators in your company? A recent Harvard Business Review article based on a study highlights four key innovation styles that can lead to success and explains how common they are across sectors. Moreover, they outline a four-part framework for ensuring your team or organization has all four styles represented.
The research revealed an individual’s preference for one of four unique innovation styles, each mapping onto a distinct phase of a four-stage innovation process. Each style has a role to play in your organization, starting with finding new problems (generators), thoroughly defining problems (conceptualizers), evaluating ideas and selecting solutions (optimizers), and implementing selected solutions (implementers).
People tend to assign themselves to different professional roles and management levels based on their innovation style. For example, generators are most often found in non-industrial occupations, while conceptualizers are most often found in strategic planning and organizational development. This raises the issue that the organizations and teams you work with are unlikely to have the right balance of styles and are not sufficiently cognitively diverse.
Understanding which employees fall into which style enables an organization to manage its innovation efforts more effectively. However, in our experience, most organizations lack some innovation styles — particularly generators. Here are four steps to help you overcome this deficiency.
1. Structure: Achieving the right ratio of innovation styles.
Managers and their teams tend to get stuck when attempting to solve complex, ill-defined problems because there is a wide divergence in potential solutions. To improve innovation, managers will first want to ask: During which stage of the innovation process do our teams get stuck? Next, managers will need to identify and amplify the missing innovation style that’s needed at that stage
2. Model: Demonstrating the importance of an innovation style top-down.
Senior leaders, therefore, have a challenge (and an opportunity) to demonstrate the importance of the needed-at-the-moment style — top down — to their entire organization. This is possible because an innovation style is a cognitive state and not a fixed personality trait and can be learned from training. In fact, a leader’s specific style is less important than their ability to shift, as needed, during the flow of the innovation process.
3. Reward: Creating incentives for problem-finding.
Because employees are rewarded for doing their job well, they tend to go out of their way to avoid problems outside their job description. This also means they go out of their way to avoid finding new problems, particularly problems that are more complex, require them to do more work, or require them to work with different departments. Our field studies suggest that there is a clear solution to this limitation: companies should make problem-finding attractive for employees by offering rewards for this activity, beyond and in addition to just providing them with the freedom to do it.
4. Train: Creating opportunities to learn about all styles.
Most education in business (and business schools) leads future business leaders to have a bias toward optimization and implementation. Why? Because they tend to expose future leaders to problems we've already solved. One way to train people towards other innovation styles is to put them in an environment with many problems.
Brain-Computer Interfaces (BCI) record brain activity and translate it into functions that can replace, restore, or supplement physical functions, assisting humans in interacting with their environment. Prevailing applications and much of the development in BCI technology currently exist within the health sciences field. Smart neuroprosthetics is a fast-developing area that could significantly impact individuals with amputations or neurological deficiencies.
BCI applications are also expanding into non-medical commercial areas like immersive gaming, neurotechnology-driven virtual reality experiences, memory recall, and mood detection.
There remain challenges related to signal processing, training sets, cost, and usability—including the required training time, user fatigue, and, with many BCIs, a lack of mobility that does not translate to many real-world settings. In addition, ethical concerns around collecting and managing brain data will likely call for new data privacy policies. However, controlling datasets of this nature could unlock several new opportunities and significant competitive advantages.
Merger and acquisition activity points to potential avenues for growth in this field. Snap has acquired NextMind, a neurotech startup developing a headband for controlling virtual objects via thought. This technology is expected to be incorporated into future versions of Snap's Spectacles augmented reality glasses. And in August this year, prior to his Twitter takeover, Neuralink founder Elon Musk approached brain chip implant developer Synchron Inc about a possible investment.
On the research front, École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and the University of Texas at Austin (UT) have developed a BCI that allows users to control assistive and Collaborative Robots. Meanwhile, researchers at the University of California San Diego have invented an advanced BCI with a flexible and moldable backing comprising penetrating microneedles. This design improves the BCI's connection to the brain's cerebral cortex.
Future applications range greatly in terms of technology readiness level (TRL), from conceptual and experimental—for example, remote communication and telepresence-controlled robotic units—to prototype and deployment. Progress in the latter TRL phases is advancing as investment increases and new startups disrupt the market. According to 2022 Crunchbase data, the top three BCI startups—Kernel, MindMaze, and Musk's Neuralink—represent over USD 820 million in funding.
To discover more game-changing technologies and inspirations for your industry, explore the full ITONICS Technology Radar or check our industry reports.
The TIME recently published its annual list of 100 groundbreaking inventions that are (positively) impacting our lives. We have picked our Top 5 highlighted below:
1. Optimizing Energy Storage - Fluence Mosaic
Massive batteries to store energy from the power grid are a crucial part of the transition to renewables. But knowing when to absorb energy and when to release it can be a complicated business. Fluence’s Mosaic makes it easier, using artificial intelligence to help battery operators—as well as owners of wind, solar, and hydro assets—know when to buy and sell electricity by predicting future prices.
2. Augmented Job Training - Magic Leap 2
Magic Leap sees a big future for augmented reality (AR) in workplaces. With this new headset, which can overlay 3D images and text on a user’s surroundings, the company is focused on the needs of employers in healthcare, manufacturing, retail and other sectors. Manufacturers, for instance, are using it to speed up training of technicians on factory floors.
3. A Solar-Powered EV - Sono Motors Sion
With gasoline prices reaching record peaks this year, it’s no wonder interest in electric vehicles has soared—despite limited charging infrastructure. But Germany-based Sono Motors wants to eliminate the hassle of plugging in at all with the solar-powered Sion, which will go into mass production in the second half of 2023. Sono Motors wraps the entire outer shell of the Sion in lightweight, affordable solar cells to boost energy capture.
4. Continuous Stroke Monitoring - Neuralert
Early treatment is key to minimize adverse outcomes, yet a recent study of in-hospital strokes found that most go undetected for over four hours. Enter Neuralert, which the Food and Drug Assocation designated a breakthrough device last year. The pair of smart wristbands use a proprietary algorithm to track arm asymmetry or weakness—common symptoms of stroke. Neuralert can detect symptoms in as little as 15 minutes, and automatically alert medical staff to spring into action. The company is targeting commercial release in 2023.
5. Detecting Destruction - Scale AI Automated Damage Identification as a Service
Drawing on streams of commercial satellite imagery, Scale AI created a new machine-learning tool that can automatically detect new damage to individual buildings. It offers geotagged links to attack reports, helping humanitarian organizations target areas of need. Scale is sharing free AI-ready datasets with application developers, as well as NATO and the U.S. government.