When Finnish gaming company Rovio Entertainment implemented data analytics as a key enabler of a new business model, they may not have expected it would also be the catalyst for a cultural transformation.

Rovio, best known in the gaming world for Angry Birds, was changing its business model in response to industry disruption. Angry Birds had been launched under the older 'pay to play' business model, but the explosion in smartphone and social media use had given rise to a new business model known as 'freemium' or 'free to play'.

By 2016, 97% of mobile gaming revenue came from the freemium model, with monetisation through in-game micro-purchases, such as virtual goods, and in-game advertising. In an industry estimated to reach US$65 billion in revenue by 2020, there were strong incentives for Rovio to change, and in this transformation, a key tool was the adoption of data analytics.  

"The impact of big data on the creative industries is relatively under-researched, so Rovio is an interesting example of how data mixes with creativity and intuition," says Yenni Tim, a lecturer in the School of Information Systems and Technology Management at UNSW Business School.

With research colleagues Shan-Ling Pan and Toomas Tamm from UNSW Business School, and Petri Hallikainen from the University of Sydney, Tim has a forthcoming paper that looks at Rovio as a case study in "actualising business analytics for organisational transformation". The aim is to understand how business analytics can drive value creation in organisations.

Data-driven design

The research is based not just on an analysis of the steps Rovio took to implement data to drive its transformation, but also with qualitative interviews with Rovio staff that underlined the strong impact the data implementation had on the company's culture.

Much of this was presented in the official documents that Rovio released as part of its initial public offering (IPO), which emphasised the strong competitive advantage the company had developed through data analytics.

The researchers were also given access to Rovio employees, and more than 12 hours of interviews were conducted at Rovio's headquarters located in Espoo, Finland, with employees across a wide variety of roles and at different levels in the organisation. What emerged for the researchers was a model that can also inform companies working in other industry sectors seeking to use business analytics to transform.

"When freemium came along and changed the industry, their business model came under pressure"

YENNI TIM

The Rovio case shows that analytics can only be successful where the insights are acted on, not just to change the business model, but also to change the way the organisation interacts with itself.

It is a view corroborated by other research. One of the first major studies of 'data-driven design' was carried out in 2011 by a team led by Erik Brynjolfsson at the Massachusetts Institute of Technology.

Based on a study of the business practices and information technology investments of 179 publicly listed firms, the research found that firms that had adopted data-driven design had outputs and productivity 5%-6% higher than those of firms that had not.

Beyond that, data-driven design had a positive impact on other areas of performance, such as asset utilisation, return on equity, and market value. In 2014, Nucleus Research claimed that for every $1 spent on data analytics, $13.01 of value was created, up from $10.66 in 2011.

Cultural change

At Rovio, the cultural change came from moving from a company where game features were perfected and released as complete, finalised products to one where analytics sought and processed customer opinions, whose feedback then guided game design and development.

This was facilitated by a cloud-based platform and a machine-learning-powered analytics engine. "Rovio was known as a company that made premium games, and this worked well and helped them establish the company," says Tim. 

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"But when freemium came along and changed the industry, their business model came under pressure, and they understood they needed to change. When you try to engage users and make them pay, you really have to understand them, so that requires analytics to tell you how long they play, how long they stay in a particular level of the game, and all this data was collected so that Rovio could understand its users and design its monetisation strategy." 

The data not only helped monetise the game within the freemium model but also improved the game experience for customers. This was because, instead of relying on designers' instincts, Rovio's design process was driven by feedback collected from the data. "This created a different mindset," says Tim. "Because the data was telling them something they wouldn't have known otherwise."

Mixed roles

It was an exercise that also democratised data use within the company and changed the way teams were structured.

Previously, Rovio was divided into teams of designers and developers, but by using data, the company recognised the benefits of transparency, which helped create hybrid team structures with mixed roles. "This had the benefit of sharing data and communicating better within small teams, where people were able to understand all aspects of the process of creating the game," says Tim.

"This created a different mindset because the data was telling them something they wouldn’t have known otherwise"

YENNI TIM

The interviews showed that this cultural shift required some change management within the company. Some of the designers were initially challenged by a data-driven way of working, while data transparency was also new to many.

"But in time the transition was successful, and Rovio went to the market in an IPO not as a mobile gaming company, but as an entertainment company," says Tim.

Six recommendations for industry professionals

1. For executives: Connect analytics investments to decisions and business model changes, rather than treating data collection as the end goal.
2. For transformation leaders: Plan for changes in roles, information sharing and decision rights when analytics becomes part of operating processes.
3. For product leaders: Use customer behaviour data alongside professional judgement when testing changes to products and services.
4. For data leaders: Make analytics available to the teams responsible for acting on findings rather than keeping access within a data function.
5. For people leaders: Include change management when teams move from decisions based mainly on experience towards decisions informed by data.
6. For strategy leaders: Assess whether analytics is changing how the organisation creates value, rather than measuring success solely through technology implementation.