Everyone is talking about implementing Artificial intelligence, Machine learning and big data in the organization. The future lies in these technologies, so there is a massive rush towards implementing advanced data science techniques and tools and using big data methodologies. In this race, the organization often ignores the importance of small data. No one can disagree that big data is essential and will help organization growth in the end. However, in this article, I want to highlight the benefits of small data projects and how it can help make fruitful business decisions.
Nevertheless, before demystifying the benefits of small data projects, let us first focus on big data projects. The big data is often characterized based on three Vs which is Volume, Variety and Velocity. Volume means the amount of the data; Variety means the types of data and Velocity means the speed. Big data gives extensive insights such as finding the hidden pattern about consumer behaviour or predicting sales using colossal data files. However, to reach those high-level insights, we need massive investment in the storage, tools, and skill set. The three Vs make big data complex and challenging to manage.
On the other hand, small data is usable, comfortable to obtain and leads to quick insights. Using small data strategically, the business can get frequent, actionable insights without investing in great tools and platforms. Small data is present everywhere. For example, an organization’s CRM system accessible to everyone has so much relevant information about customers, their segments, competitors, contact details, etc. If one can combine CRM’s insights, they can get multiple benefits for strategic business development. Small data projects require a handful of employees using small data sets and simple analytic techniques and methods to get the required results. The project duration is short, and as stated above, it does not require high-end tools.
So how an organization can get the best out of small data projects? Here is some suggestive approach:
1. Awareness – This is the first step. One needs to identify the problems, which can be solved using small data sets. For this, involvement is critical. One should keep eyes on every tiny detail. Start small and build confidence in the team. Once the team sees value, they will also look for opportunities to find problems, which can be, solve using small data.
2. Encouragement – Encourage the employees to join the data initiative. Award and reward them, who solve business problems using small data in their unique ways. It will motivate others to find the hidden data factories, and gradually, everyone will join the data-driven decision-making community within the organization
3. Discipline approach – Usually, the small data projects are simple, and sometimes it directly leads to the solution. Because of this, people ignore the usual process of a data project. Therefore, it is advisable to follow a disciplined approach, even if the answer is visible. The necessary steps of any data projects include identifying the business problem, collecting the required data, performing the analysis and finding the suggestion and recommendation.
4. Training to the employee – Training is another critical area. Small data projects are doable in every department and do not require high-end skills, but the basic training on data practices is still necessary. By providing essential training, one can ensure that everyone is on the same page while executing small data projects.
5. Quality measurement – Even if the small data projects use a smaller data set, the quality measurement is essential. From obtaining the data to implementing the results, every step should follow the standard quality control process and guidelines. It will ensure the authenticity of the outcomes.
The data-driven decision making is becoming the necessity of upcoming time. It is essential for every organization, whether big or small, to think using the data. Small data projects can be beneficial in this journey. Even if it does not lead to high outcomes, it will help achieve a smaller milestone in a quick turnaround time.