Identifying Barriers to Technology Adoption
When experiencing inertia to adopting technology, enterprises and government agencies should first identify the root cause of the resistance. Frequently, resistance comes in the form of one or more of the following organizational challenges:
- Balancing project risk and reward. Because development teams are typically rewarded for project completion, they tend to favor familiar, conventional approaches, even if newer methods represent improvements in speed and agility over older methods that are slower and more costly.
- Maintaining the status quo. Related to the previous rationale for selecting the same tools for every task because they seem simpler and less disruptive, IT teams may select familiar tools based on skill/comfort levels versus weighing new demands against all available technology options.
- Tools ahead of processes. Project teams rely on the development tools as well as complementary processes built up by the ICC over time. Lack of these best practice methods, reusable objects and management tools in the early stages counterbalance some of the productivity benefits that newer-to-market tools may provide.
- Chargeback bias. Established technologies represent the lion’s share of installed projects, and are therefore allocated a larger portion of the budget to cover licensing and support costs. In contrast, tools not currently in use within the organization may be funded by a smaller set of projects. Unwittingly, this effectively penalizes new technology adopters, even when they can demonstrate lower total cost of ownership projections for the alternative technologies.
- Architectural conformance. Top-down architectures with review boards are used to gain control over ever-changing technology and ever-growing information and systems’ complexity. Because data services frequently cross over enterprise architectural domains such as data integration and service-oriented architecture, consensus building may take longer and potentially slow down adoption.
How have global enterprises overcome these barriers? Here are three organizations we can learn from.
Energy Company Adoption Fueled by Governance and Standards
One of the world’s top five integrated energy companies has implemented data services, rather than a traditional enterprise data warehousing approach, to serve as its primary data integration strategy across the organization’s entire $100 billion upstream (drilling and refining) business. With this approach, data from hundreds of wells can be shared to optimize maintenance programs, and multiple refineries can be shared to optimize yields. To successfully adopt data services on this massive scale, the company applied a combination of powerful information architecture, information standards and centralized governance.
Architecturally, this implementation is aligned with the principles described by Gartner Research Director Mark Beyer in his published research on data services, and covered by Forrester Research Vice President, Research Director Mike Gilpin and Principal Analyst Noel Yuhanna in their recent information-as-a-service reports. The energy company initiated its adoption process with these unbiased industry analyst validations.
The data services themselves were modeled and built by a central information architecture ICC, instantiating the more than 700 business canonical models describing the key entities of this complex business. Because these reusable data services transform raw data to meet business needs, project teams that leverage them can focus 100 percent on the consuming application logic and visualization, saving time and money that in the past went to source data efforts.
To ensure that these benefits are ongoing and continual, IT governance processes require that all new development projects receive ICC approval before they are funded.
Bank Funds Early Adopters
The rapid application development competency center at one of the world’s largest investment management and asset administrators leverages data services to accelerate critical IT projects. The team uses an innovative organizational, risk management and funding model that has resulted in four completed data services projects during the first year of adoption.
As a first step, the team organized a rapid application ICC, supervised by a senior IT executive, with the mission of accelerating IT response to better meet a fluctuating global investment environment. This team identified data services as an important enabler and selected a data virtualization platform from a leading independent vendor to deliver the necessary data services. The financial services company concurrently committed to delivering the first of the four projects for the purpose of gaining a deeper understanding of the capabilities of data services, thereby starting the process of building best practices and removing risk from subsequent projects.
With the data virtualization platform acquisition, the team also secured sufficient hardware and vendor consulting services to fully enable the next three projects, in essence giving the business units subsequently requesting these projects a financial “free ride.” This helped overcome the chargeback bias identified previously, while demonstrating a real commitment to this new approach.
Telecom Maintains the Connection
After years of centralized architecture and software recommendations failing to be adopted by geographically distributed IT teams, a world leader in next-generation mobile technologies vowed to find a more efficient process. As a result, the team rewrote its charter to value equally successful adoption and intelligent recommendations.
To drive adoption, an elite new technology “SWAT” team was formed within the centralized enterprise architecture group. The SWAT team comprised staff with both vision and implementation skills. The team’s explicit mission was to find, test, procure and drive successful adoption of innovative new information technologies. Assessing the landscape of needs in light of existing capabilities, this team identified data services as its first initiative.
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