Common technology adoption blockers and challenges to innovation

As described in Innovation in the digital economy, innovation requires a balance between invention and adoption. This article expands on the common cloud adoption challenges and blockers to innovation, as it aims to help you understand how this approach can add value during your innovation cycles.

Formula for innovation: innovation = invention + adoption

Knowing how to overcome innovation challenges takes some time to discover the right methods. This article delves into overcoming technology adoption challenges in the workplace.

Cloud technology adoption challenges

Although cloud technology advances have reduced some of the friction related to adoption, technology adoption is more people-centric than technology-centric. And unfortunately, the cloud can't fix people.

The following list describes some of the most common adoption challenges related to innovation. As you progress through the Innovate methodology, each of the challenges in the following sections are identified and addressed. Before you apply this methodology, evaluate your current innovation cycles to determine which are the most important challenges or blockers for you. Then, use the methodology to address or remove those blockers.

Types of external challenges

  • Time to market: In a digital economy, time to market is one of the most crucial indicators of market domination. Surprisingly, time to market impact has little to do with positioning or early market share. Both of these factors are fickle and temporary. The time to market advantage comes from the simple truth that the more time your solution has on the market, the more time you have to learn, iterate, and improve. To shorten time to market and accelerate learning opportunities, focus on quick definition and rapid build of an effective minimum viable product.
  • Competitive challenges: Dominant incumbents reduce opportunities to engage and learn from customers. Competitors also create external pressure to deliver more quickly. Build fast, but invest heavily in understanding the proper measures. Well-defined niches produce more actionable feedback measures and enhance your ability to partner and learn, resulting in better overall solutions.
  • Understand your customer: Customer empathy starts with an understanding of the customer and customer base. One of the biggest challenges for innovators is the ability to rapidly categorize measurements and learning within the build-measure-learn cycle. It's important to understand your customer through the lenses of market segmentation, channels, and types of relationships. Throughout the build-measure-learn cycle, these data points help create empathy and shape the lessons learned.

Types of internal challenges

  • Choosing innovation candidates: When investing in innovation, healthy companies spawn an endless supply of potential inventions. Many of these create compelling business cases that suggest high returns and generate enticing business justification spreadsheets. As described in the build article, building with customer empathy should be prioritized over invention that's based only on gain projections. If customer empathy isn't visible in the proposal, long-term adoption is unlikely.
  • Balancing the portfolio: Most technology implementations don't focus on changing the market or improving the lives of customers. In the average IT department, more than 80% of workloads are maintained for basic process automation. With the ease of innovation, it's tempting to innovate and rearchitect those solutions. Most of the times, those workloads can experience similar or better returns by migrating or modernizing the solution, with no change to core business logic or data processes. Balance your portfolio to favor innovation strategies that can be built with clear empathy for the customer (internal or external). For all other workloads, follow a migrate path to financial returns.
  • Maintaining focus and protecting priorities: When you've made a commitment to innovation, it's important to maintain your team's focus. During the first iteration of a build phase, it's relatively easy to keep a team excited about the possibilities of changing the future for your customers. However, that first MVP release is just the beginning. True innovation comes with each build-measure-learn cycle, by learning from the feedback loops to produce a better solution. As a leader in any innovation process, concentrate on keeping the team focused and on maintaining your innovation priorities through the subsequent, less-glamorous build iterations.

Invention challenges

Before the widespread adoption of the cloud, invention cycles that depended on information technology were laborious and time-consuming. Procurement and provisioning cycles frequently delayed the crucial first steps toward any new solutions. The cost of DevOps solutions and feedback loops delayed teams' abilities to collaborate on early stage ideation and invention. Costs related to developer environments and data platforms prevented anyone but highly trained professional developers from participating in the creation of new solutions.

The cloud has overcome many of these invention challenges by providing self-service automated provisioning, light-weight development and deployment tools, and opportunities for professional developers and citizen developers to cooperate in creating rapid solutions. Using the cloud for innovation dramatically reduces customer challenges and blockers to the invention side of the innovation equation.

Invention and innovation challenges in a digital economy

The invention challenges of today are different than challenges of the past. The endless potential of cloud technologies also produces more implementation options and deeper considerations about how those implementations might be used.

The Innovate methodology uses the following innovation disciplines to help align your implementation decisions with your invention and adoption goals:

  • Data platforms: New sources and variations on data are available. Previously, much of this data couldn't be integrated into legacy or on-premises applications to create cost-effective solutions. Understanding the change you hope to drive in customers will inform your data platform decisions. Those decisions will be an extension of selected approaches to ingest, integrate, categorize, and share data. Microsoft refers to this decision-making process as the democratization of data.
  • Device interactions: IoT, mobile, and augmented reality blur the lines between digital and physical, accelerating the digital economy. Understanding the real-world interactions surrounding customer behavior will drive decisions about device integration.
  • Applications: Applications are no longer the exclusive domain of professional developers. Nor do they require traditional server-based approaches. Empowering professional developers, enabling business specialists to become citizen developers, and expanding compute options for API, micro-services, and PaaS solutions expand application interface options. Understanding the digital experience required to shape customer behavior will improve your decision-making about application options.
  • Source code and deployment: Collaboration between developers of all walks improves both quality and speed to market. Integration of feedback and a rapid response to learning shape market leaders. Commitment to the build, measure, and learn processes help accelerate tool adoption decisions.
  • Predictive solutions: In a digital economy, it's seldom sufficient to just meet the current needs of your customers. Customers expect businesses to anticipate their next steps and predict their future needs. Continuous learning often evolves into prediction tooling. The complexity of customer needs and the availability of data will help define the best tools and approaches to predict and influence.

In a digital economy, the greatest challenge architects face is to clearly understand their customers' invention and adoption needs and to then determine the best cloud-based toolchain to deliver on those needs.

Next steps

With the knowledge you've gained about the build-measure-learn model and a growth mindset, you're ready to develop digital inventions within the Innovate methodology.