How Big Data Can Influence Your Business Strategy

Big data is still a hugely relevant topic, although the term has become a little distorted and overused. Google Trends data indicates that hype around this topic has declined over the past five years.¹ However, the technology’s real enterprise adoption is actually accelerating.

The analysis of large data sets has the potential to transform long-standing traditional organizational practices, as well as business planning. Big data strategies are becoming essential to compete in the contemporary marketplace, and for this reason organizations should consider the following to enhance their data culture: ²

1. Understand what it means to be a data-driven organization and give the right people access to data.
2. Adopt modern technologies with insights enabled by artificial intelligence (AI), data lakes, collaboration tools, logical data warehouses, and augmented analytics.
3. Disrupt company culture by incentivizing innovation, addressing issues directly, and facilitating collaboration between decision makers and technical staff.
4. Make your organization’s data findable, accessible, interoperable, and reusable.
5. Develop data literacy so all employees can communicate precisely around key concepts.
6. Make data a core part of your business and approach business problems from an analytical perspective.

Two companies utilizing big data effectively in building their business strategies are Spotify and Coca-Cola.

Spotify

The popular music streaming service has access to over 406 million unique sources of data in the form of global, monthly active users.³ From listeners and musicians, to producers and managers, terabytes of data are produced every single day, allowing Spotify business leaders to engineer ingenious big data business strategies. With so many active users streaming songs on a daily basis, Spotify’s data alchemists are able to employ big data-driven strategies to provide listeners with music they didn’t even know they wanted to hear.⁴

In this business case, Spotify is using big data to provide solutions for their customers, but how are they using big data to enhance their business planning efforts?

Spotify collects an enormous amount of data, from song choices and favorite genres, to less obvious factors like choice of headphones, when song volume is turned down, and when the Spotify browser window is resized.⁵ The mountains of data Spotify acquires each day helps users find content according to their tastes, but it’s also used by the company to customize their marketing strategies.

Spotify’s ‘Thanks 2016, it’s been weird’ advertising billboards drew attention around the world. By analyzing collections of big data, Spotify identified some striking scenarios of listener behavior and created billboards that poked fun at these through clever copywriting. One of the billboards famously read: Dear person who played ‘Sorry’ 42 times on Valentine’s Day, What did you do?

Schnoor, A. (May, 2020). ‘Understanding Spotify’s marketing mastery’. Retrieved from Better Marketing.

But Spotify’s approach to – and use of – big data has landed them on front pages and in hot water with users. Spotify’s users lashed out in 2015 due to widespread dissatisfaction with large-scale updates to the service’s privacy policy. Users became outraged by the apparent lack of regard for their privacy, with around 75 million active users leaving the service.⁶

In 2021, Spotify received patent approval on technology to monitor user speech and background noise in order to curate their music recommendations. In response, more than 180 musicians signed an open letter criticizing the company and asking for a commitment never to use the technology. Spotify in turn responded by saying they had not implemented it and had no plans to do so.⁷

Coca-Cola

The Coca-Cola Company is the world’s largest non-alcoholic beverage producer, selling more than 3,500 products across more than 500 brands to consumers in over 200 countries.⁸ With these kinds of production, distribution, sales, and consumption numbers, inordinate amounts of data are being produced every second by Coke consumers all over the globe.

The Coca-Cola Company was one of the first globally recognized, non-IT companies to employ big data solutions to build business strategies. In 2012, their chief big data insights officer, Esat Sezer, said, “Social media, mobile applications, cloud computing, and e-commerce are combining to give companies like Coca-Cola an unprecedented toolset to change the way they approach IT. Behind all this, big data gives you the intelligence to cap it all off.” ⁹

In 2009, Coca-Cola released the Freestyle vending machine, allowing users to mix more than 100 flavors on the spot via a touchscreen, using technology originally designed to measure dialysis and cancer drugs for patients. These machines were installed in movie theaters, shopping malls, and fast food outlets all across the US, gathering information about consumers’ flavor choices.¹⁰ In 2020, the company responded to concerns around the spread of COVID-19 by enabling customers to choose their drinks via their phones, scanning a QR code to gain access to the interface.¹¹

Coca-Cola has used the data collected by the Freestyle vending machines to research and plan the development of their next product. The data revealed which flavor people wanted the most and in 2017, the company delivered the final product: Cherry Sprite.

Pathak, R. (Jul, 2021). ‘How Coca-Cola uses technology to stay at the top?’. Retrieved from Analytics Steps.

In another example of Coca-Cola’s big data application, the beverage company designed a unique way to find potential new consumers of its iced tea brand, Gold Peak. Using image recognition software, the company trawled and identified social media posts that depicted users enjoying iced tea or competitor brands. As a result they were able to target potential consumers with Gold Peak ads.¹²

Coca-Cola also uses AI to analyze thousands upon thousands of pieces of social media content in order to better understand demographics in different regions. This helps the company learn when, where, and how people consume their various products.¹³

Big data trends for 2022

The Coca-Cola Company and Spotify have two of the largest consumer bases in the world, giving them access to more data than most other businesses. Even though your organization might not harvest as much user data as these two behemoths, big data applications have the potential to guide your business strategies and improve your planning. These are some of the key trends that will influence how organizations employ data.

The right data analytics

With data being created and collected at an exponential rate, organizations need to find ways to identify precisely what data should be analyzed. Data analysts with these skills will save companies a lot of time and effort, on top of providing more relevant insights.¹⁴

Predictive analytics

The right data is essential to take advantage of predictive analytics. This uses statistics and modeling techniques to enable companies to forecast potential opportunities, trends, failures, and bottlenecks.¹⁵ Predictive analytics has applications ranging from HR, finance, and healthcare to retail, real estate, and manufacturing.¹⁶

Data sharing

New data-sharing technologies are making it possible to buy and sell information securely in cloud-based marketplaces. Coupled with privacy-preserving innovations, this has provided an opportunity for organizations to monetize potentially valuable data they would otherwise not have shared for security or regulatory reasons. According to Forrester Research, 70 percent of data analytics decision makers are increasing the amount of external data they use, while 17 percent plan to do so in 2022.

Gartner predicts that, by 2023, organizations that embrace data-sharing will outperform competitors.

Farrall, F., et al. (2022). ‘Tech Trends 2022’. Retrieved from Deloitte.

Chief Information Officers (CIOs) should familiarize themselves with these key advances in privacy technology that are enabling this new age of information sharing:¹⁷

• Full homomorphic encryption – Encrypting data before sharing it, so it can be analyzed but not decoded
• Differential privacy – Adding noise to data, making it impossible to reverse-engineer
• Functional encryption – Keys enable select users to view select parts of encrypted text
• Federated analysis – Sharing data analysis insights rather than the actual data
• Zero-knowledge proofs – Proving knowledge of a value without revealing the value itself
• Secure multiparty computation – Spreading data analysis across many parties means no one party has access to all the inputs

Low- and no-code tools

While technical skills remain invaluable when working with data, cloud providers are developing machine-learning applications and workflows that are democratizing data science. Amazon Sagemaker Canvas is one example of a low-/no-code tool that enables employees across a broader range of business functions and skill sets to search for, extract, and utilize data.¹⁸ These tools also offer the potential for subject matter experts to develop machine-learning solutions without coding knowledge.¹⁹ Nevertheless, IT staff should be trained in explaining and deploying such tools so that the rest of the workforce can take advantage of them.

Vertical cloud computing

Vertical cloud computing refers to cloud-based solutions, APIs, and accelerators specifically designed for a particular business industry, process, or model. They’re built to be easily adopted, with the potential to be customized using legacy or tailor-made solutions for differentiation. The benefits for businesses include the opportunity to increase agility and efficiency and lower costs by offloading business processes to the cloud. To take advantage of this trend, business and IT leaders must collaborate, with each developing a greater understanding of the other’s roles in order to identify which technologies are unique and highly competitive to the business. Anything else can be provisioned from cloud or software providers.²⁰

If these trends overwhelm you, becoming equipped with the expertise to utilize big data in your company is the first step to joining this revolution. By learning how to collect and analyze big data, and finding a way to incorporate it into your strategic business plan, you’ll be enabling your company to market more effectively, explore new revenue opportunities, provide better customer service, improve operational efficiency, or leverage new advantages over competitors.

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