Google's growth strategy: knowledge generation and latent semantic indexing

Google Case Study Analysis

Originating as a search engine technology that found its initial customers in the companies who would eventually become competitors, Google is transforming the online advertising business model while funding the development of entirely new generations of information-intensive applications. Clearly from the case study it is not in Google's best interest to move into a consolidation role within the media and entertainment industries, or even strive to become an entertainment hub. The Time-Warner model of growth through acquisition has proven to be costly, unable to respond to changing market dynamics quickly enough, and forced into premature obsolescence by the highly topical nature of its content. The case studies show clearly that this role of media hub from a technology standpoint and industry aggregator from a mergers & acquisitions (M&a) strategic standpoint is definitely not the strategic vision for Google. What emerges instead is a compelling vision of delivering process-centric knowledge and information to both individuals and businesses. In analyzing the case study, the future vision of Google becomes clearer when the interlinking of knowledge, generated from the index of data, becomes the foundation of the next generation of growth strategies. It is the intent of this analysis to provide the foundations of growth for Google's future strategy, including potential M&a targets in key markets.

Latent Semantic Indexing and Modelling - Critical to Google's Success

Google Labs (2007) provides an overview of the technologies that Google Labs is producing today specifically in the area of Natural Language Processing (NLP). The founders of Google specifically began their work on optimization algorithms in this area, focusing on latent semantic indexing as an approach to categorizes content by inferring its role in process-centric schema, further adding context to the data by also looking at links to and from the data set. The case study only provided a cursory overview of this powerful technology; in fact when the Google Labs page is explored, it is clear that Google finds the complex interconnections of data produce knowledge, and while the company would never state it publicly today due to intense competitive pressures with Yahoo and Microsoft, knowledge generation and retrieval is the next technological jump the company must be considering, five or more years into the future. The implications of being able to quickly correlate many initially unrelated data elements into a concept that can in turn be integrated into a broader knowledge set could be the foundation of Google's next generation of services as well.

Competitors today offering SaaS-based Applications in this area?

Attracting, selling and servicing customers; finding new customers; retaining existing customers; developing new products with customers' help through the use of the New Product Development & Introduction (NPDI) process

Customer Relationship Management (CRM) and customer-facing product development processes including the NPDI.

Yes - Salesforce.com in the area of CRM; NPDI by SAP on their OnDemand platform

Group communications and the ability to have a conference meeting anytime, anywhere; critical in new project development

Collaboration

Low-end: Web Conferencing)(High End: Product development team globally)

Yes - Many vendors have SaaS-based solutions in this arena.

Analyzing data from website traffic, including trending on click-through data and visitor's unique attributes

Analytics (Google has a trial version of this today; yet could go up-market with this into web traffic analytics)

Yes - Several; yet no one has perfected optimization of Google AdWords yet or AdSense; these will be the most likely services Google will launch in Analytics first on a fee basis.

Security of websites, data storage and Internet traffic

Security and Enterprise Scalability

Google has extensive internal knowledge in these areas and can easily create new services based on their lessons learned. Google is considered to have one of the best internal technologies for managing network security and reliability in the software industry.

Process-centric workflows specifically in the areas of web-based, records-based and unstructured content are a major unmet need in many companies.

Enterprise Content Management

By using NLP technology and the Google taxonomy, an enterprise content management (ECM) service could easily be created.

When the process-centric approaches to organizing data into knowledge is considered, the large, very profitable markets of CRM, Collaboration, Analytics, Security and Enterprise Scalability, and Enterprise Content Management all become very attractive from an investment perspective by Google. The prioritization of these specific opportunities needs to be defined by the total available market, level of competitive pressure on pricing and product strategies, and the need for growing the existing Google technologies sufficiently to support further growth strategies. When these criteria are applied to these process-centric areas, the following prioritization of new services emerges. First, Collaboration is by far the most critical new process segment for Google to move aggressively to either with internal development of new applications or through acquisitions. Second, CRM is a natural extension of the Collaboration investments, as the processes for tracking customer relationships including the ability to apply knowledge to attracting, selling and servicing customers is already proven on the SaaS platform by Salesforce.com. Third, Collaboration and CRM would serve as a strong foundation for integrating data and knowledge into an Enterprise Content Management service that would build upon the many insights gained from creating applications in the first two areas. As a fourth priority the development of Analytics over and above the free service it is today to a more thorough set of tools specifically aimed at delivering greater insights into web traffic and its implications on customer segmentation. These first four product or service strategies build upon one another to create an enterprise application vision for Google, which will turn the fundamental search and content aggregation technologies into a set of services none of their competitors would be able to match for years. Google migrating to a process-centric provider of knowledge and tools to use those insights would be further supported by the last service, one specifically focused on security and enterprise scalability, capitalizing on the depth of knowledge and expertise internally specifically in these areas.