In this article...

• Adopting a new technology starts with education.
• Adoption should support a business case.
• There are various approaches to implementing cognitive technology.

Putting cognitive technology to work is easier than you might think, but how?

First, some background. The cognitive era is an ongoing movement of sweeping technological transformation. The impetus of this movement is the emerging field of cognitive technology, radically disruptive systems that understand unstructured data, reason to form hypotheses, learn from experience and interact with humans naturally. Success in the cognitive era will depend on the ability to derive intelligence from all forms of data with this technology.

Cognitive computing is perhaps most unique in that it upends the established IT doctrine that a technology’s value diminishes over time; because cognitive systems improve as they learn, they actually become more valuable. This quality among others makes cognitive technology highly desirable for business, and many early adopters are leveraging the competitive advantage it affords.

In a recently conducted IBM market study, we investigated more than 600 early adopters who are putting cognitive technology to work. Our report, The Cognitive advantage: Insights from early adopters on driving business value, examines emerging patterns of early adoption. These patterns reveal a blueprint of sorts for future adopters.

The question then for you and your organization is simple: How do I get started?

Adopting a new technology starts with education

Cognitive initiatives come in all shapes and sizes, from transformational to tactical and everything in between. What the most successful projects have in common, no matter how ambitious, is they begin with a clear view of what the technology can do. Therefore, your first task is to gain a firm understanding of cognitive capabilities.

The cognitive era is here not only because the technology has come of age, but also because the phenomenon of big data requires it. Computing systems of the past can capture, move and store unstructured data, but they cannot understand it. Cognitive systems can. The application of this breakthrough is ideally suited to address business challenges like scaling human expertise and augmenting human intelligence.

Becoming a cognitive business looks different for almost everyone. Although a common perception is cognitive technology is complex and difficult, that is not necessarily true. While some early adopters start with ambitions to transform their organization or industry, most start relatively small. Talk to many successful early adopters and you will hear some variation on the theme of “I want to improve one specific operational process.”

The point is, it is helpful to avoid assumptions regarding what adoption will look like for you. It is better to keep an open mind during this information gathering phase. Here are resources that will help give you a solid foundation:

Envision the possible and define your ideal outcomes

Judging by the success of early adopters, it's no surprise more and more organizations are looking to adopt. Many are grappling with how and when, but why is most important.

No one starts down this path expressly to adopt cognitive technology; the whole point is to improve the organization. Adopting cognitive technology above all else should align to business priorities. Successful early adopters identify a problem, then build a case for how solving that problem will support specific outcomes like saving money, gaining customers or increasing revenue.

Good planning will result in the selection of a specific and strategic use case. Usage patterns tend to fall into four major categories that play to the strengths of cognitive technology. First, cognitive technology is often used to enable innovation and discovery by understanding new patterns, insights and opportunities. Second, it is often used to optimize operations to provide better awareness, continuous learning, better forecasting and optimization. Third, to augment and scale expertise by capturing and sharing the collective knowledge of the organization. Finally, to create adaptive, personalized experiences, including individualized products and services, to better engage customers and meet their needs.

One temptation, however, is to pursue cognitive technology for the technology’s sake. "Most of the failures we've seen are when you start with the technology instead of the business case," according to an IBM cognitive technology architect. "There are so many things you can do with cognitive technology, and people get really excited. But you need to focus on what impacts your bottom line.”

Conversely, overthinking can lead to inaction. According to a CEO that leverages cognitive technology, “a lot of companies are over-analyzing what they should be doing. They want a fully detailed design and guaranteed quality of output, but it doesn’t work that way. It’s better to start small with a good idea, and from there scale out and scale up. There is no universal template for success, but focus on persistence is a proven formula.”

One IBM expert described this strategy as preventing the perfect from becoming the enemy of the good. In some cases, the best advice is to select a use case quickly to overcome the inertia created by a misguided desire for perfection. Adoption can mean something as basic as tapping a pre-built cognitive application. Starting small does not prohibit future expansion, and strategy can evolve over time.

"Often what’s difficult is the trade-off of fixing current pain points and doing something that aligns with long-term vision,” according to an IBM cognitive strategy specialist. “This is where people can struggle. It’s easy to be short-term focused. The challenge is to marry fixing the current problem with making sure it is the right move for the long term. So prioritizing the right use case that balances these things is the big challenge, and it’s where we can help the client the most."

As you develop your strategy, share ideas with other forward thinkers within your organization—their support is essential—or brainstorm with a member of the IBM team.

Choose the best implementation approach for you

Once you gain a realistic understanding of what cognitive technology can do, and specifically how it will help your business, it's time to choose your approach.

1. Deploy cognitive solutions and apps.

Many early adopters know exactly where they want to install cognitive technology, so they embed readily available cognitive offerings into existing workflows. The lever of this approach is a pre-built cognitive solution, like Watson Virtual Agent or Watson Explorer. These products are already coded, and only require installation and integration with data sources up front.

2. Build your own cognitive apps.

Developers can build their own cognitive apps through Bluemix, IBM’s cloud platform. More than 40,000 developers are building with APIs (application programming interfaces). The Watson Developer Cloud offers common language descriptions, demonstrations, case studies and starter kits for each API. “It’s good to let developers get in and play around,” said an IBM cognitive expert. “Because the technology is so new, it’s almost impossible to explain everything up front. You learn a lot by doing.”

Watch: What is a cognitive API?

3. Collaborate to create cognitive solutions.

If your strategy is ambitious and transformational, you will likely need to collaborate on unique and customized solutions. IBM offers various advisory programs designed to support these types of initiatives in which the adopter aims to change whole business functions or ways of working and competing. These programs often deliver prototypes, or proofs-of-concept, that simulate your desired cognitive-enabled state using your own data.

To collaborate with cognitive technology adoption specialists, contact a member of the IBM Cognitive Solutions Team.

Checklist for adoption:

• What are my desired outcomes?
• How will cognitive technology help me achieve these outcomes?
• What is my long-term vision with this technology?
• Do I have strong executive support?
• Can my organization adapt existing processes and roles?

• Do I have the necessary skills within my organization?
• Do I have the IT environment I need to get started?
• Which path is right for me: build, deploy or collaborate?
• How will value be measured?