Turning big data into action

Steps to convert Big Data into actionable insights

The true worth of data lies in its ability to facilitate impactful decision-making. To extract value from data, it is crucial to swiftly convert it into meaningful insights and actionable steps that can be repeated consistently.
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1. Decide what to produce

To prepare for work at an insight factory, define your goals and the questions you need to answer to achieve them. Prioritize questions that address significant economic opportunities and can guide practical actions. Configure the factory to produce only those insights. For instance, a retailer identified a decline in sales from 12% of its customers in certain markets and used targeted local market merchandising tactics to reverse the trend after exploring the root cause.

2. Source the raw materials

Start with the best data that is immediately available, and create a selective data mart to produce insights quickly. Add more data sets over time. For example, a retailer began with transactional POS data and added third-party customer data, syndicated competitor data, and public sources. It enriched these insights over a year by adding social media and location data and financial information from credit card providers.

3. Produce insights with speed

To achieve productive action in analytics, speed is crucial. This can be achieved by setting finite time limits, using repeatable analytical models and automation, and adopting a start-up mentality that prioritizes quick decision-making and a test-and-learn culture. Small, nimble teams with a combination of strategic, analytical, and technical skills are more effective than slow-moving committees. Offshore talent can also be recruited to execute structured analysis continuously at a lower cost.

4. Deliver the goods and act

Immediate action can be taken based on the information available now. For instance, if data shows that milk and eggs are usually purchased together, they should be placed side by side on shelves. However, it is essential to understand what front-line managers require to take action. Providing them with data analysis they can't use is counterproductive. Sales and marketing personnel must be part of the process and given simple tools to act on insights. Tools like customer scorecards or store operations health monitors are beneficial, but it's best to listen to managers' needs and respond accordingly.
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