The Data, Analytics and Insight Process
Welcome to Brijj! The better way to build Insights.
A data, analytics or insight project is the journey a Data or Insight team takes from a question all the way to an outcome. Effective projects depend on the connection between technical teams and the business users who consume their outputs. Brijj provides functionality to manage, track and improve every step for both data creators and consumers all in one platform.
Below, we will outline the steps in the Insight Generation process and provide links to the specific Brijj Functionality & Knowledge Base articles which provide more detail.
The Insight Generation Process in Brijj
Gathering Requests, Questions or Business Needs
The first step in any data, analytics or Insight project is the request, question or business need that is identified by your consumers. An effective project begins with ensuring that initial requests are gathered correctly. You need to know;
- What is needed at a high level
- What the intended business decision, action or outcome is
- Whether there is an expected outcome from the insight
- When the insight is required
- Who the insight is for
Having these pieces of information provided upfront is essential to the building of accurate requirements and the further successful delivery of the project.
Brijj makes this process simple using Best practice guided Request Forms.
Proposed Models: Collaborative building of requirements
The second, and in many respects most important step, in any data, analytics or Insight project is the building and agreement of specific requirements. Requirements should be informed by the initial requests but should go into greater detail about what is to be delivered. It is important that this be a collaborative effort between those who need the insight (consumers) and those who build them (creators)
When building requirement they should be documented along with consumer agreement on;
- Scope of Project
- Agreed Outputs
- Expected action or decision that is to be informed or conducted
- Parameters of analysis
- High level detail on models, techniques and visualisations to be employed
- Delivery Timeframes
- Criteria for project success
- Any privacy considerations
Having these pieces of information provided, documented and agreed is essential to the efficient commencement of projects and the reduction of rework.
Building Models: Agile Development of Outputs and Deliverables
Once requirements have been built and agreed, the building work of insight begins. During this phase it is important to keep collaboration and communication channels open between consumers and creators to enable an agile approach to the development work and keep stakeholders engaged throughout. Topics which may need to be discussed include;
- Review of output drafts
- Changes to scope
- Unforeseen issues with modelling
- Changes to Delivery Timeframes
- General Discussion
Delivering Insight: Central Insight Storage and Deliverable Discussion
Nearly all Insight projects have an output of some kind. Be it a live production model, a Dashboard, An Excel file, PowerPoint presentation or simply a "number". Having these outputs openly accessible, where appropriate, and attaching discussion around these is important to provide a full view of organisational insight and grows the data-led culture that all organisations need.
Consider the following when it comes to Delivering your insights.
- It should be absolutely clear to your stakeholders where to go to find their outputs and the available insights generated by their organisation.
- Recording discussion around deliverables and keeping it accessible and linked to deliverables allows further insight creating a feedback loop further improving organisational understanding.
Post Project Follow-up: Insight Quality, Utility Assessment and Action / Outcome Evaluation
The most commonly missed step in the insight generation process is consistent follow up around the quality, utility and application of Insights. You need to know three things once work is delivered;
- Was the work delivered to standard?
- Did the work allow stakeholders to do what they needed?
- What was actually done as a result of the work?
Without consistently doing this follow-up work it is difficult to be fully informed on where your organisation needs to improve its capability and data culture and makes proving ROI on your Insight activities more difficult.
Also be sure to view the Dashboards available for summary information on the status and quality of your work.