Deep Dive: The Information Asset

The E&M industry depends on information and data. Trends such as mobility, streaming, social media and personalized channels have changed customer demands, which means the E&M industry and its players need to become information-centric. Only this way they will be able to act quickly on new trends, create new distribution channels and adapt their business models if needed.

Andreas Quandt
Andreas Quandt Practice Leader Information economics PwC Switzerland
Information – and the ability to transform it into knowledge – is crucial to gaining competitive advantages and staying relevant in the market. Two principles guide the transformation into an information-centric company: 1) information and data are corporate assets, to be managed accordingly; 2) business, compliance and technology must be aligned to assure legal, legitimate handling while also generating value.

The major challenges of transforming to an information-centric company are the same as those of 2010 when the The Economist wrote in 2010: “…the technical, infrastructural and even business-model implications are not well understood right now.” Most companies struggled with transformation, because of a common mistake – In the first step, they focus on technologies such as Hadoop and Cloud, rather than on actual business goals – e.g. expanding the customer base to a specific group or entering new, more profitable markets.

Indeed, transformation to a data-centric company is possible only if the sequence is reversed. First, strategy must be defined. Second, governance must be implemented. Third, analytics capability must be established. These are inextricably intertwined, as shown below.

Strategy – The value of information and their establishment as corporate asset

Especially in E&M, organisations are challenged by digitization: more distribution channels and formats, the search for individualism, variety of content, the change cycle, and the speed of trends. Data can help to address these challenges, to add more value and gain profit, but only if they are understood as corporate asset.

Many organizations understand that data can help: to create new products and services, to understand customer needs better, to reduce production costs and improve distribution channels. Still, often they do not recognise and treat their data as assets. To change this is goal of the data strategy, which establishes the following three attributes for data: data is something that (1) generates probable future economic benefit; (2) is exchangeable for cash and (3) controlled by the organization.  

The first attribute– generates probable future economic benefit – defines which data are required (i.e. to be created or collected) to achieve business goals in future. The second attribute – exchangeable for cash – defines the worth of data, whether they should be shared with third parties and the importance of their protection. The third attribute – controlled by the organization – is the most difficult to establish because it requires a modern data governance that helps to control the organization’s data, which today are bigger, faster-changing and more diverse than ever.

Governance – Manage information transparently, and foster innovation

Data quantities are booming, its potential value to organizations is growing, and its regulations (such as the EU data protection reform) are changing and C-suites find it increasingly important to manage the data they hold. This, plus the often missing transparency of the data life cycle, leads to the establishment of modern data governance which is shaped by business requirements that are defined as part of the data strategy.

Data governance means different things to different people. Some focus on data protection, others on technical topics or data quality. But almost never is data governance understood as a support of data-based innovation, therefore a business enabler for all data-centric companies. Governance not only helps minimise legal risks and public exposure, but also gains value and acquires competitive advantage.

To help organizations reclaim their data, modern data governance needs two major components:

The organisation – Alliance  of Business, Compliance and IT

An increasing awareness of the value of data and the painful recognition of an inability to take advantage of the opportunities that it provides, the handling of data and their responsibilities must be regulated within a company and anchored accordingly in the organization. There are three key factors to doing so.
First, there must be close coordination of procedures for decision-making and escalation within the organization. These processes must be defined clearly, to assure timely decisions and innovation without increasing risk.

Second, decisions about data need to balance demands of business, compliance & information technology (IT). The new organization needs to facilitate the dialog between these groups and establish decision-making bodies on the various levels of the organization. It is also important to coordinate with existing roles and processes, to keep transformation efforts to a minimum.

Third is sponsorship. A board member must be a leading sponsor and management backing is indispensable. This means CEO, CFO, CSO or similar, but not an IT-executive. Data governance can succeed only if business takes full ownership of processes and policies relating to the creation and management of data. IT has often led data governance initiatives in the past: these have tended to focus on tools, rather than on the needs of the business with a limited business value as result.

Policies and specifications – It is not all about the law

These are based on the determination of rules, standards and criteria to evaluate data over the entire life cycle of data, from generation to extinction. There are three major blocks to it: quality, availability and protection.

Data quality is essential to interpreting data correctly, and to create value for business processes and improved decision-making. Data should be accurate, complete, timely, credible, consistent, clear, understandable, verifiable and interpretable.
Data availability specifies when data are available for use within specific business processes. There should be multiple key-performance-indicators (KPIs) to monitor and improve handling of large, complex data landscapes.
Data protection includes legal policies to adapt to current law, and policies specific to each organization. Examples are legitimacy (socially accepted norms) and corporate interests (sharing of data with third parties or intellectual property). This block can also contain policies regarding data security, the technical means for protection of data in an organization.

Analytics Capability – Creating value through new insights

Strategy and governance are two important steps to gain value from data and use it as new raw material for the business: Data strategy sets the scene for business development, and it defines the expected value of data. Data governance provides the power of control to manage data as corporate asset and measures progress towards a data-centric organization. To take these beyond the theoretical, and to justify investments, another capability is needed: data analytics. This includes:

(1) hypothesis-verification of new, data-centric businesses through use cases;

(2) value-generation through data analysis & reporting as part of established processes, such as business intelligence (BI) and enterprise performance management (EPM);

(3) compliant exchange of data, and interaction with third parties.


The impact on the Swiss market

"Data are becoming the new raw material of business: an economic input almost on a par with capital and labour."

Craig Mundie, Head of Research & Strategy at Microsoft, The Economist, Feb. 2010. 

Socio-economic changes such as digitisation, the rise of generation Y (the millennials) and globalization have broad impact on products, service offerings and customer interactions of every organization. National players in E&M will succeed only if they react quickly to market trends and if they build reliable client relationships.

Turning information into knowledge helps to (1) define new distribution channels, such as streaming on demand, digital newspapers and eBooks, (2) provide new offerings such as time shifted TV, 360°-movies, augmented reality and interactive storytelling, where TV and video games merge, and (3) adjust business models, because of the expected micro-segmentation of the market and new revenue streams such as pay-per-use, crowdfunding and personalized marketing.

At the same time, there are risks. Society in general and customers in particular are becoming ever more aware of information’s impact in our connected world. Irresponsible handling of information is increasingly less tolerated by customers – in the worst case, it leads to brand damage and lawsuits. Recent modifications of European data-protection laws (which will soon be exported to Switzerland) make this more relevant than ever. Transparent use of data, and fair use of customer information, will be unique selling points. These will build reliable client relationships, a major advantage in future.