Organization models for commercializing Big Data

Organization structures for Big Data

Mobile operators must define the right organization model for managing large Big Data projects. The model needs to effectively align the demands of the business with the technology requirements needed to support those demands. Such initiatives necessarily involve an element of cultural change within the operator, as they require collaboration across conventional functional and business unit silos.

The importance of organization structure

Commercializing Big Data products requires an operator to integrate a strong IT analytics capability with externally-facing marketing resources. Deciding how this integration is organized and led is a critical part of successful Big Data initiatives.

In our Organizing for Big Data page we look at the overall issues of organization structure. This post looks at the different organization models.

There is no ‘cookie cutter’ approach to organizing Big Data teams. Operators begin at different points along the evolution path, with different existing organizational structures and levels of maturity, and varying sets of capabilities.

Arriving at the appropriate cross-functional, cooperative model for leveraging data assets involves some degree of compromise and trade-off between the various stakeholder groups.

 What are the preferred organization models?

There are three discrete organization models that are currently being implemented across those mobile operators who are actively pursuing Big Data initiatives:

  • IT systems-led (including a dedicated data analytics group)
  • Business function-led (with Marketing and/or Finance as the lead functions)
  • Matrix organization (a hybrid IT-Marketing-Finance group)

Post - big data monetisation chart 2

Given the clear potential for creating new and sustainable revenue streams from Big Data initiatives, it is likely that the majority of operators will elect to form matrix organizations over time as a critical mass of Big Data resources is established.

The importance of senior leadership

This structure implies a senior executive leader who understands the overall operator business and has a clear line of sight into C-suite priorities.

In addition, this leader must have considerable authority to make key decisions about investment priorities with regard to both IT and business resources, a high degree of respect among both business and IT stakeholders, and the ability to balance short-term business needs with longer-term goals for building out the necessary data capabilities.

As such identifying and attracting such talent (if unavailable internally) is a potential drag on progress in gearing up to attack the Big Data opportunity.

The war for talent is not confined to the fierce competition for data scientists!

Where are the opportunities to monetize Big Data?

Post - where can you monetize big data graphic 2

Falling profit margins from voice, messaging and data services are driving mobile operators to find ways to monetize Big Data, thereby turning their existing information assets into new sources of revenue.

New competitors, increasing competition

The competitive environment for mobile operators is radically different to the market place in which they first launched their services.  A new breed of competitors has arisen as a result of a blurring between traditional device and service lines, and companies such as Apple and Samsung control whole areas of the app space.

In addition, a raft of OTT players are driving the commoditization of basic services, and a wave of messaging, music and video providers are winning the battle for consumer mindshare and hence taking increasing revenue share.

As network costs continue to increase, while traditional revenues stay flat, margins are getting squeezed. Intense competition from multiple directions is therefore driving the operators to seek new sources of revenue.

New lines of business enabled by Big Data

In order to assert their position in this new competitive world, mobile operators are pursuing new lines of business that have the potential both to monetize the value of their big data assets and to entrench the operators as a pivotal player in their markets.

Post - big data chart 3

Customer insights – aggregated and anonymised mobile subscriber data has extreme value for a wide array of commercial and public services organisations: retailers (store location planning, campaign design), local government administrations (urban planning), advertising companies (outdoor media mapping), sports and entertainment venues (audience profiling).

Data hosting – by virtue of their service provider legacy, strict industry-wide regulatory framework and data protection obligations, the mobile operators have developed very strong trust relationships with consumers and businesses alike. This opens up the prospect of operators utilising their data assets in order to host security and authentication-based services on behalf of financial institutions, government agencies and e-commerce companies. Identity management, access control and user authentication are all part of the service portfolios being developed by the leading US and European operators.

Third party applications – rather than viewing companies which provide digital services over the network as competitors, increasingly operators are seeing them as business partners. In principle, any service that requires a set of enabling utilities such as customer billing, problem resolution, security and authentication services can be interfaced directly with the host systems and databases in the mobile operator environment. The demand for these hard-wired services will grow rapidly as e-commerce, mobile healthcare and machine-to-machine (M2M) applications become ubiquitous.

Moving towards a two-sided business model

The incumbent network operators therefore have the opportunity to create a ‘two-sided’ business model, whereby they leverage the latent worth of their unique assets – namely their captive subscriber data and their accumulated reputation capital.

  • Firstly, they create more intimate relationships with their existing ‘downstream’ mobile subscribers, through a relentless focus on customer experience management and service personalization
  • Secondly, they form ‘upstream’ strategic partnerships with both private and public sector organizations, underpinned by a new product and service portfolio founded on the principles of privacy, trust and security

Executed well, this two-sided approach is virtually impossible for any communications service provider without a self-provisioned network to emulate successfully.  The pathway for the network operators to assume the central position in the rapidly-evolving mobile services eco-system is wide open.

Our approach for putting the customer at the center of this business model is outlined in our Monetizing Big Data page.