For order of magnitude return on investments, your data strategy must be driven by the business strategy. Whilst others may pay lip service to this concept, our strategists at Insight possess the rare combination of vast business experience combined with wide and deep data skills.

Our years of experience partnering with businesses across a wide range of industries has shown us that in order to succeed in a data rich world, we have to start with the business strategy. Our 1-3-5 Customer Data Journey framework has been built with this overall principle in mind. We call it the 1-3-5 Journey because it focuses on the short (1 year), medium (3 years) and long term (5 years) data and information capabilities for the business.

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Components of the Business Intelligence Journey

Our data journey has 8 key components. They are depicted in an overlapping loop below to show that this is a process that needs to be continuously be revisited as the needs of the business change. A structure is important, but it is a guideline, and should be flexible enough to adapt to changing realities.

We begin with an audit phase, focusing on understanding your business goals. You’ve probably already done a lot of thinking around this, so the key here is for our strategists to ensure that they understand these goals. We then work with your business to work out what data is required to support these goals. We’ll advise and brainstorm with you to define a consolidated 1-3-5 plan for your data needs. At the end of this audit phase, we have a 1-3-5 data requirements document, detailing the data that is required, whether it is already available, where it is stored and what the options are for collecting it if we don’t already have it.

We know from the audit phase what data we need – the next step is defining how we structure the data to enable reporting and analytics.

What does the source data look like? If it isn’t available, what is the plan to make it available? Do we need to build capture and/or workflow apps for automation?

What are the transformation steps required to get the data from its raw format in the Data Capturing and Collation step into its final Data Structure for reporting and analytics?

Once we have the data flow set up, how will we manage it to ensure integrity, security, accuracy, validity and governance?

What will our analytics environment look like? We need to think about business areas, scorecards, exception reporting, alerting, trend analysis, predictive analytics and machine learning, drill downs to KPI drivers – everything required to enable business users to quickly understand business issues, and act fast to fix them.

Business Users have to be self sufficient, and be able to act fast to quickly and easily get to their insights. How do we ensure that the environment they are working in has as much easy and intuitive self-service capability as possible?

Data and Information is only as useful as the human intelligence acting on it. Many organisations have vast amounts of data with very few people who know how to use it to track and meet their business goals. Our Data Literacy programmes empower business users to understand how data can support their day to day work, allowing them to spend more time on analysis and making decisions based on facts and figures.

  1. Audit Phase
  2. Data Structure
  3. Data Capturing & Collation
  4. Integration & Synthesis
  5. Data Management
  6. Analytics & Reporting
  7. Self-Service
  8. Data Literacy