Building focused analytics solutions that address business opportunities

Data Analytics is an enterprise capability that requires the right combination of skills and the right governance model. It takes more than statistical/advanced maths mastery for a data analytics team to have the right decisive impact on the organising they are serving with actionable insights.

There is a clear business problem to be solved, Line of Business stakeholders are involved and are the drivers for data insights to be produced.

You even have identified how business processes and/or decision making processes would be amended once insight are delivered. What next then? Just produce the insights! Indeed yes and this functionality allows a Data Analytics team to both master the analytics techniques producing accurate data insights as well as empowering Line of Business people to input/understand/anticipate deployment of those insights.

 

Our Pathfinder‘s Data Analytics team has years of industry experience that has enabled us to adapt international best practice in Data Mining and Data Analytics to build insights that are actioned by Lines of Business (LoB) people.

The following stages are completed in an iterative fashion: 

 

It is about bringing Data Analysts and LoB people together to identify the business question that needs answering by leveraging data and to start anticipating the change in business practice that the data insight would make possible (what would you do differently if you were to receive this insight?). We always start with the Business Question!

Completing a full review of the different relevant data sources that are relevant for the particular business question from a quality/volume/history/accessibility perspective. It includes validation with Line of Business people (again!). This review may lead to an amendment of the business question. The current data sources will put a limitation on answering question A but we can answer question A* which delivers value to LoB.

Data engineering (data cleansing, aggregation, merging etc) activities and data modelling activities are required to produce the actual insight. An agile collaborative approach with LoB is required to regularly test the quality/actionability of the insights as they are being prepared (be it a dashboard or a predictive stream).

When the Data Analytics team and Line of Business people have the confidence that relevant, actionable, accurate insight are to be deployed in real life, it is crucial to plan for this deployment addressing both data/technology factors and change management factors.

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