Executive Guide to Cognitive Computing Part 5

Recommended Strategic Planning and Considerations for Cognitive Computing Projects

In order to proceed one must start to define the use case (business problem) and more importantly what is the question or questions that need to be answered.  As mentioned earlier cognitive computing is a new focus on knowledge or information automation vs. Process automation that we are familiar with in traditional technology systems.

Defining the intention of the project?

This may seem apparent but organization can get caught up in the excitement surrounding cognitive computing and lose sight of what type of problem needs to be solved or resolved.

1. Type of questions/information to be asked or analyzed?

2. What type of dialog/conversation to be supported?

3. Integration with pre-existing systems?

4. Number of potential users?

5. Corpora or Corpus Size (Type of Data and # of Documents) and level of complexity ?

Defining the Objective

Having a clear idea of the outcome of the project is the next step.  This ensures that the proper cognitive technology is applied.  Are you analyzing text? Are you trying to assist a call centre agent   Are you attempting to automate a question and answer conversation?  The objective must be clear:

  • What type of problem is trying to solve?
  • Who will be the user?
  • Are there multiple types of users? and what are their expectations?
  • What issues will your users be interested in?
  • What do they need to know?
  • Will they need to answer questions like How and Why?
  • What is the objective based on knowledge and data? (vs. process)
  • Type of knowledge that will be pivotal to corpus? (segment of domain or business/industry)
  • Will the system be needed to provide assistance? (Citizen or Agent)


Defining the Domain to analyze:

  • Helps to identity data sources as well as SMEs that will need to be involved
  • Can the objective narrow the domain focus?
  • Is there domain taxonomies, ontologies and catalogues?
  • Have you identified additional data sources not typically associated with solving problems in that domain? (i.e. learned by experience)

Recommended Next Steps on your Cognitive Computing Journey?

Assess the Cognitive Computing Maturity of the organization

Knowing where you are today vs. where you want the organization to be in the future is critical.  Identifying gaps and priorities in how and where Cognitive Computing can be used provides a clear idea on what you have invested in the past and what you will need to invest in the future.  A Cognitive Computing maturity assessment is a quick way to start to understand the level of effort required.  As shown in the illustration it can quickly guide decisions in planning and investment in this new technology.

 Cognitive MM

Figure 2: Cognitive Computing Maturity Model Assessment Example

Engage with IT and IM

Since cognitive systems will rely on accessing more forms of information: text, pictures, voice, sensor, geo-special and traditional sources; business and IT/IM must work together.  Although business may lead the initiative where all that information will be coming from will require a broader more cross-functional team to help develop domains of knowledge.  Include organizations that manage the ECM environments as well as other forms of information.  Understand where Open Data is coming from and what are the governance issues associated with combining many forms of information together.  With IT/IM and the lines of business working together the outcome of any project will be more successful.  However; it must be clear who is the ultimate owner of the project.

Cultural and Organization Readiness

Cognitive like Analytics or Big Data require a shift in the organization culture.  Once groups and individuals learn that they can ask complicated questions and get answers in a shorter period of time then receptivity to a new innovate technology will be positive.

Never belittle the importance of organizational change and fundamental training for the new projects or programs.  The organizational change management plan must be aligned to the domain and objective of the cognitive project.

Prioritize on Business Problem to resolve

Cognitive systems are predicated on solving specific problem.  It is critical that a clear business problem is identified.  Typically, it starts with a question or area that needs to be better understood.  Traditional approaches of IT defining the solution for the problem may not necessarily work.  What is needed is a cross-functional planning team that sees the business problem to be solved from many directions.  This team needs to have executive sponsorship and participation as well as multiple lines of business.  This is due to the fact that cognitive systems rely on more sources of information that multiple lines of business may have.  IT will be required to prioritize and plan on accessing the sources of information (data sets).

Identify Key Questions to answer (How? and Why?)

Traditional analytics technologies have been able to answer questions like What? Where? and When?  However, cognitive systems can answer those type of questions as well as How? And Why?  In order to answer those questions all there has to be a coordinated plan and team that can help to define the questions then start to assess where the information is in order to answer those questions.

Rapid Proof of Technology Exercise

In order to quickly assess the capability of Cognitive Computing a proof of technology session should be planned.  This encompasses a limited scope workshop that tests the viability of answering a question.  It is strongly recommended that this approach is done since it addresses all the points raised above.

Skill Development

Lastly, since Cognitive Systems require a new method of programming (algorithmic) skills may have to be developed and enhanced within the IT organization as well as the lines of business.  This ties in with cultural change.  The dynamics of Cognitive Systems are different from traditional IT systems and project planning.  Without proper skill development any system will not succeed.

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