By Celeste L. Corrado, MSIS, MBA
Strategy, Innovation and Information Systems Expert
The need to revise and retool competitive intelligence functions within organizations is rapidly becoming a priority given the exponential increase in the volume and complexity of data and the on-going demand for timely strategic insights. This article provides a glimpse of currently available information technology tools designed to enhance data collection and analysis and suggestions on how to incorporate them into Competitive Intelligence (CI) practice today.
Drivers of Change Create Catalysts for Innovation
Big technology drivers, such as computing mobility and the convergence of the physical and digital worlds, are resulting in seismic industry shifts. The residual effect is an explosive growth in the volume, velocity and variation of information and an insatiable appetite for real time meaningful information. These drivers of change represent very real challenges for CI practitioners. However, incorporating new and emerging information technology tools and techniques into the competitive intelligence cycle can offer solutions to these challenges by boosting the speed, quality and delivery of competitive intelligence (Figure 1).
Figure 1: Drivers of Change Create Catalysts of Innovation
In today’s dynamic business environment, success is increasingly dependent upon the ability to gain timely access to strategic and competitive insights in combination with an organization’s agility and ability to rapidly respond to those insights. Although these success factors are not new to competitive intelligence practitioners, meeting these demands are increasingly more difficult given the vast and explosive growth of data. The volume of information is growing at an average rate of 60% annually, generating roughly 5 zettabytes of data by the end of this year (Figures 2 and 3). In addition, data is increasingly more complex, containing both structured (e.g. text) and unstructured data (e.g. photos, videos, and social media), further challenging our ability to perform data analysis. These challenges raise some key questions for competitive intelligence practitioners:
- How do we deal with the volume and complexity of data and the demand for synthesizing and delivering relevant insights at a much faster pace?
- How do we address these challenges without compromising the quality of information?
Figure 2: Zettabyte vs. Gigabytes
Figure 3: Data Projections
Fortunately, exponential increases in computer processing power have provided the foundation for a revolution in new information technology tools and capabilities that enhance and augment our ability to keep pace with the speed, agility and high quality informational needs of organizations. These tools provide the ability to collect, store, cleanse, process, mine, filter, and ultimately synthesize large complex data sets (Figure 4). In addition, advances in human computer interaction and artificial intelligence software have made information technology tools more accessible, affordable, intuitive and user friendly. For example: search and retrieval tools that facilitate the collection of relevant information, social media tools that enable connections to large populations of people, and information visualization tools that facilitate the ability to “see” abstract data or “hidden” patterns, trends and insights in large data sets.
Figure 4: Enablers of Search/Retrieval and Analysis of Large Complex Data Sets
Benefits of Information Systems Tools & Techniques
Leveraging the right information technology tools throughout the CI cycle can create a force multiplier for CI practitioners. Below are just a few of the benefits these tools are beginning to provide:
- Affordable & rapid access to new sources of primary information (e.g. social media)
- Improved quality and speed of research results
- Enhanced ability to access & synthesize large data sets
- Visualization & analysis of new & abstract data forms (e.g. social networks, internet connections etc)
- Discovery of hidden & unexpected insights through tools that facilitate 2-way interactions
- Enhanced organization, storage and retrieval of search results
- New methods of distributing & enhancing CI results
As is the case with current data collection and analysis tools, no one tool provides a comprehensive solution. To harness the power of these tools requires the right combination of tools and techniques. Many of these tools are currently in use, and many are under development and evolving, but all require practical hands-on experimentation to understand their strengths and weaknesses and where, in the CI cycle, they add the most value. However, a willingness to explore and interact with these tools can yield unexpected and hidden insights that could not be feasible using traditional CI tools and techniques. A practical knowledge of these tools can significantly augment all aspects of the CI cycle including search/collection, retrieval, analysis and distribution processes.
Figure 5: Integrating Information Technology Tools in the CI Cycle
Incorporating Emerging Information Technologies into the Competitive Intelligence (CI) Cycle
The following section provides a snapshot of tools and technologies that could be seamlessly integrated into the CI cycle and the competitive intelligence practitioner’s arsenal of tools.
A. Data Collection & Information Retrieval
Social media tools provide an opportunity to rapidly, affordably and virtually access and connect with people and networks that would be difficult to access by any other means. This is an efficient and affordable method of sharing and collecting primary information and intelligence from vast networks of people. We are just beginning to realize the value of this rich source of information, not just for collecting and sharing information but mining the rich data that comes from the network itself (figure 9). In addition, it is a highly effective method of quickly disseminating intelligence across networks.
Information Search & Retrieval
Information Visualization (infovis) tools are available that speed up and enhance conventional searches by visually organizing data. Below is one of many infovis tools, TouchGraph, used in conjunction with a Google search. In the example below (Figure 6), the search inputs used were <bioenergy + biomass + biofuels>. TouchGraph synthesizes and categorizes the results into an easy to digest visualization making it easier to drill down to relevant information. From this visualization, it is easy to click on the graphic to drill down to a specific subtopic of interest— effectively narrowing search results to relevant sources.
Figure 6: TouchGraph Visually Enhances Search & Retrieval
Figure 7: Google News Aggregator Visually Enhances Search & Retrieval
B. Data Analysis
To address data volume, complexity and variation challenges, data scientists are continuously developing and refining algorithms that analyze both structured and unstructured data: seeking out patterns in the datasets, providing the means to intuitively categorize large data sets and facilitating the ability to mine the relevant data. These capabilities are the enablers that make it feasible to navigate through large datasets, such as the pools of human genome data, and locate, validate and retrieve “relevant” data sets.
Building upon these sophisticated algorithms are information visualization tools that synthesize and organize large data sets. Patent analytics and patent landscape visualizations are an example of robust infovis applications that are in use today, rapidly evolving and gaining in popularity. The visualization in Figure 8 is a “view” of the patent landscape when searching on the key word <Bioenergy>. Color indicates similar patent groups while the size of the polygon indicates the number of patents contained within that category. This type of visualization enables the user to plow through thousands of patent data to more easily drill down and interact with those patents contained within the subcategory of interest.
Figure 8: Scopus- Visual Tools to Enhance Patent Research & Analytics
C. Trends Patterns and Insights
Visualization tools are particularly valuable to CI practitioners because they help us to “organize and see” abstract data such as social networks. This is extremely beneficial in providing the capability to interact with complex data sets and discover hidden patterns and trends.
The following are examples of evolving infovis tools that allow us to “see” abstract data sets. The infovis tool in Figure 9 is LinkedIn’s InMap tool that depicts relationships between connections within social networks. This infovis allows the user to intuitively “see”, “explore”, “interact with”, and “analyze” LinkedIn networks. These types of tools are available for a wide range of networks including Facebook, Twitter, InstaGram etc., each offering unique insights into networks of interest. The infovis in Figure 10 is extremely advanced and depicts a visually compelling internet security system designed to scan for intrusion detection in real time.
Figure 9: In Maps – Visualization of LinkedIn Networkst
Figure 10: Daedalus- Visualization of Internet Intrusion Alerts
The need to revise and retool the CI function is rapidly becoming a priority, given the growing demand for speed, agility, affordability in obtaining relevant information and the exponential growth and complexity of data. Many information technology applications such as information visualization and social media tools are currently available and can be seamlessly integrated into the CI cycle process.
Some key questions for competitive intelligence practitioners:
- Could the evolution and proliferation of information technology tools and techniques help create newer more agile CI platforms, tool, and techniques?
- Could advances in information systems and technologies create a force multiplier by lowering the cost and increasing the fidelity of CI solutions?
- Could these solutions pave the way for the next generation of CI programs, expertise, techniques and tools?
Answering these questions requires a willingness to continuously learn, discover and explore new advances in information technology while continuously “re-tooling” and perhaps “re-imagining” the CI process to include these capabilities as they become available. Embracing information technology innovations can significantly enhance our ability to access and mine rich data sets and meet the ever increasing demand for quality information delivered rapidly and affordably.
About the Author
Ms. Corrado is a competitive intelligence professional with expertise in strategy, advanced technology (R&D) development, innovation and information systems. She offers a unique perspective on the challenges and opportunities of incorporating new information technologies within the competitive intelligence collection and analysis cycle. In addition, she is the founder of Vizeon Solutions, providing results-driven innovation, competitive intelligence, technology, and business solutions to Fortune 500 clients. Prior to Vizeon Solutions, Ms. Corrado developed, launched and led the start-up of a commercial “innovation platform” for a large Defense Contractor. The incubator has resulted in a multi-billion portfolio of new ventures. She is credited with developing a lean, agile competitive intelligence program tailored to the company’s innovation objectives and funding availability. For more information please contact the author at firstname.lastname@example.org