Menu Close

Why Big Data doesn’t have to be big to be effective

Big Data doesn’t have to be big. Organisations need to become data-centric to operate effectively and data quality is more important than quantity.

Why Big Data Doesn’t Have To Be Big To Be Effective

Big Data has long since transformed from a buzzword to a business reality. Companies are using Big Data to drive smarter business decisions, helping them react faster to market changes and customer demands. However, many companies are daunted by the ‘big’ in Big Data, believing that only by gathering a massive quantity of data can they achieve value from their data.

This means too many companies are failing to capitalise on the actual value of the data they currently have because of a mistaken belief that a smaller quantity of data simply isn’t enough to derive actionable insights.

The truth is, the quality of your data is far more important than how much data you have. Quality data that’s analysed carefully and strategically leads to useful insights. Companies that can implement those insights will start to see their competitiveness increase.

However, the big question for many companies is how to ensure the data they’re collecting is valuable. One way to do this is to collect data from reputable sources, as well as by sharing and matching different data sources. Whatever the data type and source, there are three key requirements for data to be valuable.

It must be relevant, dynamic, and timely:

  1. Relevant:

    Collecting data about everything and anything is counterproductive. It’s far more important to collect data that relates directly to the challenges you need to solve.

    Relevant data leads to natural conversations and workflows to power the decision-making process and customer experience. It lets you discover potential opportunities and act on them to improve processes and interactions exponentially.

  2. Dynamic:

    It’s essential to collect dynamic data across the right channels and to keep conversations continuous. If the data isn’t dynamic, the conversation ceases to be insightful, diminishing its value.

  3. Timely:

    The most relevant and dynamic data in the world won’t be useful if it’s collected and analysed too late to be actioned. It’s essential to get the right data at the right time so you can get insights that are useful in the moment. Information and insights must be available on demand.

As long as your data fulfils these three requirements, there’s no need for it to be massive in quantity. Even a small amount of data that is relevant, dynamic, and timely, can help your business transform by making data-driven decisions. These decisions are more likely to be strategically and objectively correct in terms of delivering growth and sustaining a competitive edge.

Don’t wait until you reach some arbitrarily determined amount of data before you start using it to improve your operations and your bottom line. Start now with the data you have, then continue to build on this foundation. This way, you can extract real value from your data immediately and into the future.

Leave a Reply