The start of the year is the ideal time for SMEs to incorporate a Big Data strategy to gain competitiveness and profitability.
While the digital acceleration caused by the pandemic reached many Spanish SMEs, many still need to undergo a thorough digital transformation centered on the massive and coherent management of large volumes of data. The reality is that most of them bet on digitalization: 70% of these companies trust in digitalization and are already considering investing in it over the next three years.
What makes a Big Data strategy useful for these types of companies is that it often provides answers to questions that the organization itself had not previously considered. After analyzing the information, organizations can focus on their own problems proactively while also leveraging them to generate new opportunities, more efficient operations, increased profits, and enhanced customer loyalty.
Often, the 5 Vs of Big Data (Volume, Velocity, Variety, Veracity, and Value) lead SMEs to face the challenge of determining if they can extract real and high-quality data from large, changing, and complex data sets.
It frequently happens that SMEs encounter many sources and types of data, making integration increasingly difficult. Data sources can range from digital marketing campaigns and social media to third-party data, IoT data, structured data (CRM/ERP), unstructured data (documents, videos, audio, etc.), and semi-structured data (spreadsheets, reports).
On the other hand, handling a large volume of data makes it challenging to achieve efficiency quickly: collecting, cleaning, integrating, and obtaining high and accurate data quality rapidly when data changes at speed requires high processing power to avoid drawing conclusions from erroneous information.
In this scenario, SMEs must address 4 stages that guide a data strategy:
- Definition of a Problem: Translate the business problem and identify data sources. Clearly understand the problem to be solved by asking: What is my main objective? What business problem do I have? What do I want to explain using data?
- Data Preparation: Select useful data and extract it from its sources. A central question here is: How much customer history do I have stored? Who owns the data? Big Data consolidates data from numerous sources and applications. Conventional data integration mechanisms are generally not up to this task, requiring new strategies and technologies. During the integration process, it is necessary to incorporate data, process it, and ensure it is formatted and available.
- Data Storage: Big Data requires secure storage for data that also meets processing requirements and necessary processing engines. Cloud storage is progressively increasing in popularity because it is compatible with Big Data technological requirements and is accessible to SMEs.
- Data Study: Analyze variables to understand their behavior and relationships. A data-oriented culture requires systematic decision-making based on a “data cult.” Investment in Big Data for SMEs is truly profitable when data is analyzed and utilized correctly, exploring new opportunities and building data models based on machine learning and artificial intelligence. Once the model is built, it is possible to predict reality from any available information.
The beginning of a new year is the ideal context to launch a digital transformation and Big Data strategy in SMEs; it is the first step towards a profound disruption in a complex and changing context that demands a radical shift in mindset and strategic focus from these companies.
By Julio Cesar Blanco – January 10, 2023
