Understanding the DREPD

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Understanding the DREPD (hereinafter, the Session) is a hands-on session designed to get its participants started understanding the DREPD. The Session is the fifth of ten sessions of CNMCyber Bootcamps (hereinafter, the Bootcamp).

Using the DREPD, differentiating concepts and experiments, as well as induction and deduction


Outline

How to use the DREPD

Dadi.png

DREPD is a cycle that divides enterprise development into four (4) batches or stages. The name is drawn from the four (4) abbreviations making up the name as below

  • D - Discover - This is the first stage in DREPD and involves discovering the challenge and shortcomings facing the enterprise. Enterprise Discovery comprises of all activities undertaken to identify areas within the enterprise that can be developed further
  • R - Research refers to all activities undertaken to process the data discovered in the fist batch. This allows the Enterprise understand its current position and existing infrastructure to determine what changes need to be made.
  • E - Envision is the 3rd batch in Enterprise Development that covers all activities needed to conceptualize, design, scratch, model, map, plan, project, and/or detail the DREPD's outcome and/or finalize the architecture or layout for to tackle the shortcomings identified in Enterprise Discovery.
  • P - Plan - enterprise planning includes all activities needed to create and deliver the Pattern's outcome based on its architecture or layout made in enterprise envisioning.

Enterprise discovery relies heavily on Data available to the organisation and team. Simply put, the team needs to first understand the Enterprise well to discover its challenges, shortcomings and areas that need to be developed. In this regard the enterprise can not only rely on the traditional informational gathering tools. There is need to incorporate data analysis form both internal and external environment in which the organisation operates in.

Access to this data in most Enterprises is somewhat limited and slow owing to the varied data points and sources. Additionally, Traditional data collection methods are too rigid, take moot much resources and are very for thus affecting the quality and accuracy collected this way. Organisations should therefore invest heavily in Information Technology and tolls to make data collection and analysis timely and accurate.

Once the discovery and analysis batches have been completed successfully, the next stage involves drawing up a blueprint of the preferred image. It is only by picturing the ideal picture that the organisation can proceed to Design. ' Designing the solution is more straight forward as it involves identify the changes that need to made and steps that can be undertaken to change the current state of affairs. It however requires input and collaboration of the whole team to be successful.

Once the [[enterprise modeling] is complete the enterprise is ready to implement the solution designed. The management phase is critical and must be managed well to ensure success. All departments and top management should be involved in implementing the solution. The implementation team can be in-house and drawn from all departments to minimize costs associated with external consultants and to help the workforce own the process.

Management can be rigorous ranging from the minute changes in workflow to complex changes such as using new software and tools. The implementation team needs to use an approach that would have the least effect on business disruption. Additionally, they should consider a process that allows for a fall back should the new systems fail tow work or generate the expected outcome.

How to differentiate concepts and experiments

A concept is a mental image or understanding about a distinct entity in regard to its features. It is what the mind envisions when that entity of object is mentioned. Different people will will understand and perceive ideas in a different manner.

An experiment on the other hand is a scientific procedure undertaken to understand an idea or demonstrate a known fact.

From the above general definitions, experiments can be used to further explain a concept or test its validity. For example, the force of gravity is a concept that all humans are familiar with. There are so many experiments that one can conduct to explain the force of gravity including dropping objects to the ground. CNM Wiki mode of learning makes use of experiments and other practical excercises to explain concepts.

How to differentiate induction and deduction

Inductive.jpeg

In theory both Induction and deduction enable an individual form an opinion or understand a subject

In logic, induction refers to refers to drawing a conclusion by exploring the available information. It is more general in the sense that it moves from specific observations to developing more general conclusions or theories. Inductive reasoning employs the bottom - up approach

Deductive reasoning on the other hand is more specific in the sense that it moves from general observations to testing more specific hypothesis. It uses elimination method and is drawn form the word 'deduct' which means to subtract or remove. Deductive reasoning emplys the top-down approach by beginning with a theory or topic of interest, developing and testing hypothesis to confirm (or reject) those theories.

Discovering the Data is the successor session.

Materials

Recorded audio

Recorded video

Live sessions

Texts and graphics

See also