A lot has been discussed about Big Data, and how important it is in a data-based market that requires constant data management for business development. However, emerging from the same scenario, the concept of Small Data has been introduced and is receiving some attention from the market.
Today, organizations must have a data driven culture. The market no longer accepts decisions and strategies based solely on intuition and guessing. Everything must be defined based on concrete, safe and real information collected from all stakeholders.
Small Data emerges at a time when companies are less interested in how much data they have, but more on the quality of this information. After all, with the huge amount information available, it is important to elect what is in fact fundamental to build effective strategies and what is just occupying storage.
A Gartner study predicts that, by 2025, 70% of organizations will change their focus from Big Data to Small Data, prioritizing analysis tools and implementing more accurate Artificial Intelligence solutions, that are less dependent on large volumes of data.
What is Small Data?
Small Data is the strategy that focuses on the quality of collected information, not the volume. The goal is to have only relevant information that will truly influence strategies, actions, and campaigns.
In the market today there are many tools capable of dealing with large volume of data, whether collecting, storing, or interpreting it. However, there is a big chance that most of this data will not be useful for decision making.
Yes, it is important to have a broader vision of market data. Nonetheless, Small Data will accurately filter this data. Without a quality process aligned with quantitative process, companies will lose valuable insights and will not attend the fast-decision-making process required by the market.
How to analyse Small Data?
There is a difference between Small Data and Big Data analysis. As we are dealing with a more incisive approach and less scaled analysis of human factors, it becomes more important the presence of a real person behind this analysis.
If in one hand Big Data can be left in the hands of automated tools, on the other hand Small Data will require the integration of technological intelligence and team member abilities.
After all, tools used on the everyday job, specially on Customer Success, are excellent sources of information to understand the business’ persona. This analysis must focus on data that are simpler and more concrete, that helps identifying opportunities, increase processes’ efficiency and optimizes customers’ relationship.
How to apply Small Data in business?
For one of the most important experts in this field of study, Lindstrom, many companies were able to overcome a bad business phase thanks to Small Data strategies. He highlights the Lego case that faced a challenge is the latest years: children and teenagers found Lego too outdated.
Instead of gathering Big Data from the entire consuming market, they chose to analyse and collect Small Data only from the audience that was still consuming their products.
With less volume of data and more quality information, they were able to understand that the biggest appeal for young people was to be good at what they do, master the challenges of the game, accomplish missions, and share their scores.
Deep down, it wasn’t about entertainment anymore, it was about resolving challenges and comparing their accomplishments with their network. From this conclusion, they decided to redesign their pieces and this, together with other initiatives, saved this almost centenary company from collapsing.
Focusing on qualitative data, on a micro perspective, allowed Lego to understand what it had done wrong and redirect their strategies. Even so, it does not mean that Small Data works for everyone.
To understand the best practice for your business, schedule a talk to one of our consultants and see how we can help you innovate in your business and remain relevant on this everchanging market.