Three misconceptions when dealing with Big Data

• Big data is always better: One common misconception about big data is that having more data always leads to better insights and decision-making. However, the quality of data is more important than the quantity and having large amounts of irrelevant or inaccurate data can lead to incorrect conclusions and decisions.
• Big data is only for big companies: Another misconception is that big data is only useful for large corporations with huge amounts of data. In reality, businesses of all sizes can benefit from data analytics, as long as they have a clear understanding of their business goals and the data they need to achieve them.
• Big data is always objective: While big data is often seen as an objective source of information, it is important to remember that it is still subject to human biases, business rules and errors. The way data is collected, processed, and analysed can influence the results, and it is important to be aware of these potential biases and take steps to minimise them.

The term “Big Data” has been banded around for some time but has experienced strong growth in usage over the last few years as organisations and key stakeholders become aware of its true value, applications and end output, enabled by rapid progression of technology. It is a key area that we have tracked at QPE as thematical financial partners, since raising our inaugural fund in 2020.

Big data refers to substantial amounts of information generated by businesses and associated stakeholders. It encompasses everything from marketing prospects, sales data, and social media posts to confidential and regulatory data collected. The challenge for businesses is to collect, cleanse, process, and analyse this data to drive actionable insights that can drive business decisions.

Contrary to popular belief, large corporations do not necessarily have big data under control. The sheer quantum of data, spread over a complicated multi-dimensional matrix including different products, services and geographies; and the fact that data is often stored in systems and programs that do not sync well with each other, makes it challenging for businesses to manage their big data in a way that provides useful insight.

According to a UK Government report, the big data sector is expected to grow at >20% pa to 2025, spurred on by a better understanding of the need and opportunity, as well as advancements in technology such as AI and powerful software such as Snowflake and Databricks. The advancement of AI in particular has made certain functionality far more accessible but data integrity and accuracy remains an issue, though this is changing.

Big data offers organisations the potential to unlock huge value opportunities. For example, by analysing marketing and customer data, a business can gain a better understanding of their target audience and tailor messaging as well as products and services accordingly to improve the return on investment on sales and marketing expenses. They can also identify trends and patterns that help in predicting future behaviours and changes in the market to drive future change. Big Data can also help businesses identify tangible operational efficiencies. For example, by analysing supply chain data, businesses can optimise delivery schedules, reduce waste, and improve inventory management, therefore unlocking cash.

However, big data needs to be coordinated, synthesised, and analysed, which places significant requirements on hardware and software, as well as skilled analysts who have years of experience in extracting, consolidating, cleansing, analysing, and interpreting data. Accuracy of such analysis is also paramount, which drives a need to select the right technology/consultancy firm to partner with.

The usage of data has to be governed properly. There are regulations in place to ensure that proper authorisation is undertaken being data is carefully collected, stored and managed. This presents an inherent conflict between big data and data regulations such as General Data Protection Regulation, “GDPR”. Big data aims to collect and process as much data as possible to make decisions based on it. GDPR, on the other hand, ensures that minimal data is used for a clear purpose. In some instances, the further processing of personal data for different purposes other than the original intention can take place. Compatibility needs to be assessed on a case-by-case basis where the relationship, the expectations of the data subject at the time of collection, the context, and the nature of the data should be considered. This requires experience and a background in dealing with such data.

As an investor, QPE is a believer in big data, but done properly. We partnered with tech-enabled customer focussed data analytics consultancy, Sagacity (sagacitysolutions.co.uk), in mid-2021. The business then acquired REaD, which was a highly complementary business to expand competencies. Sagacity, which enjoys strong double-digit growth, supports enterprise clients with a range of customer data analytics such as prospecting data, value-based management, revenue leakage and billing analysis, as well as GDPR compliance.

Anita Dougall, CEO of Sagacity adds “We continue to see strong demand for our end-to-end customer data analytics offering, which generates our enterprise clients double digit RoIs. We use our own data, client data, proprietary software and data analytics tools to offer support services around financial management and customer value generation to enterprises across a broad range of sectors, including regulated utilities, with customers including Sky, Tesco, Boots, Staysure, Virgin Media O2 and United Utilities. Our strength lies in joining the dots between data, people, policies, processes and systems to uncover significant opportunities for our clients”.

The team at QPE have invested significant time on the wider space and we hope to bring our experience and expertise in data, digital transformation and technology to help other leading operators in the space. With the big data sector expected to grow exponentially over the next few years, we believe it is essential for businesses to effectively collect, process, and analyse big data to drive business growth and success.