The Gartner® Hype Cycle™ for Innovation Management Techniques, 2021 identifies data-driven innovation as a technique that will increasingly drive your organization’s growth, inform decision-making and advance competitive advantage. The future of innovation practices is progressively relying more on data-enhanced innovation that augments existing processes. Decision-making backed by insights garnered from data ensures a stable spine and accelerates the development of digital innovations that align with organizational strategy.
Why Is Data-Driven Innovation Important for Your Decision-Making Process?
Data is becoming available to a greater extent, faster. In addition, lower data collection and storage costs have resulted in big data becoming readily available, which can be challenging for innovation practitioners to translate at speed. Monitoring and transforming big data in the end2end innovation process is a valuable asset that sharpens strategic focus and unlocks new possibilities for products, services, and organizational processes.
Organizations must respond to market changes swiftly and precisely, and data-driven innovation offers a practical solution that translates vast amounts of data. Providing you and your team with the right information at the right time for the right reasons enables quick and accurate responses that drive competitive advantage.
How Can You Maximize the Potential of Data-Driven Innovation?
By integrating data-driven techniques into existing innovation processes, your innovation team can support fact-based decision-making and generate robust innovation strategies.
Many companies practice an idea-based approach like design thinking and human-centered design. Data-driven innovation can elevate these conventional idea generation techniques by helping teams understand where to focus their efforts. By interlinking data and design thinking capabilities, you can identify opportunity spaces for innovative products, services, and business models much faster and with a higher success rate.
How Can You Integrate Data-Driven Innovation Into Your Organization?
The Gartner® Hype Cycle™ for Innovation Management Techniques, 2021 identifies data-driven innovation techniques as crucial for future competitive advantage establishment. Currently, data-driven innovation is positioned to move into mainstream employment in the next 5-10 years, and organizations must begin to position themselves to leverage this development by cultivating:
- a data-driven culture
- organizational governance that supports data-driven innovation
- technology that collects and organizes data into a single view across the organization
How Can ITONICS Support Data-Driven Innovation?
The ITONICS Innovation Management Platform offers a single point of truth where data is easily collected, organized, analyzed, and managed. The systematic digital framework enables cross-organizational transparency and alignment by allowing innovators to link information, knowledge, and action. Collaborating across geographies and business units can be achieved effortlessly and promote a culture of innovation based on data-driven insights.
You can use the ITONICS Platform to empower your team with the right information at the right time and enable sense-making and strategic focus through the ITONICS Radar, Portfolio, and Roadmap modules.
As the world’s leading Operating System for Innovation, ITONICS provides organizations the flexibility to radically upgrade the way they innovate. We inspire, guide, and accompany innovation leaders such as adidas, Audi, KPMG, Johnson & Johnson, Mondelez, and SAP on their innovation journey.
Together with our clients, we shape the future by providing a systematic framework and single point of truth to steer innovation efforts. In doing so, we remain dedicated to staying at the forefront of innovation management, integrating emerging technologies and methodologies on the fringe of what’s next into our offering to empower everyone to innovate.Get started today!
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Gartner, Hype Cycle for Innovation Management Techniques, 2021, 12 July 2021, Jackie Fenn et. Al.
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