Our Approach - Data Analytics Projects

Our approach is "Soft issues first, Technology and Infrastructure second".

We focuses on first creating the 'soft' factors required for the success of the Data Analytics Project and building consensus with the Client on key issues.

After these have been completed, we will proceed to the actual project execution and focus on the technology aspects of the project.

BUILDING CONSENSUS

Pre-Planning Stage

These are issues that the Client will have primary control over as they pertain to issues within the Client's firm. We will play an advisory role.

Create the Data-driven Decision Making Culture

The adoption of a data-driven decision-making culture is crucial to ensuring that the organization is committed to supporting the project and has the correct mindset to ensure that they will fully utilize the project once completed.

If the company does not have this culture or does not commit to creating this culture, the project will most probably fail.

Identify Internal Champions among the Stakeholders

The internal champions are crucial to ensuring that there is sufficient commitment and resources allocated to the project. These projects can take a long time and consume a lot of resources without much to show at the beginning.

Without a strong internal champion, it is very likely that the project will eventually fizzle out and face a premature early demise.

Project Scope Definition Stage

Define How Value will be Created and Evaluated

We need to define how the project is expected to bring value to the firm in terms of solving real business problems, and how such value will be evaluated.

This is crucial to setting the right set of expectations for all parties involved.

Define the Problem to be Solved

What is the business problem that we need to solve?

Clearly defining is problem is crucial to ensuring that we are focused on a problem that is well-defined and feasible.

Identify the Right Talent Required in the Team

We need to define what are the skill sets and talents required for the team, and to develop a plan for securing these talents and skills.

UNDERSTANDING THE BUSINESS

Business Analysis Stage

We spend a lot of time at this stage to understand the business. We put on our "Business Analyst" hat here to focus on understanding and analyzing the parts of the business relevant for our data analytics project.

Every data analyst and data scientist/engineer on our project team will be fully engaged in this part of the project. We will not proceed to the next stage until this Business Analysis Stage is complete.

Many data science projects fail because the data scientists/engineers work in silos and do not understand the Client's business.

GETTING TO WORK...

Prototype Stage

Identify the Right Data Required
Develop Data Collection Methodology

What is the data that we need to collect and how can the data be collected?

It is essential that this process be as automated as possible.

Clean the Data

How do we clean the data as efficiently and effectively as possible?

It is essential to make this process as automated as possible.

Analyze the Data

How do we analyze the data? What tools do we use?

The analysis method has to be linked to the business question, as well as the amount and quality of data available.

LET'S CREATE VALUE...

Action Stage

Create Actionable Ideas

What business actions can we take with the analysis that we have done? What changes do we have to make to our strategy or operations based on the data?

All analysis is only valuable if there is some positive business action that we can take.

Implement and Test Ideas

We implement the business actions and strategy changes.

Review Impact
Review Protoype

Monitor the impact of the actions and changes taken. Based on these results, review and refine the model.

We must validate the usefulness and appropriateness of the model based on real-world data.

IF THE PROTOTYPE PASSES THE TEST...

Deploy

Deploy the model for everyone to use.

Maintain

How do we maintain the model? Who will be responsible for maintenance?

LET'S IMPLEMENT...

Client continues building the Data-driven Decision Making Culture

This culture is the key to ensuring the long term success of the Transformation. This is entirely the responsibility of the Client but we will assist as much as we can.

This is a long-term effort as it takes a long time to change the values and habits of people.