Significance of Patent Landscape Analysis

 

Patent landscape analysis is a comprehensive analysis of patents and scientific literature. An analysis is focused on the research area given by the client. A Patent landscape analysis shows the white space in the research area, IP trends to figure out the density of activity, and technology decay and rise. Patent landscaping is suitable for planning research in virtually any area of technology. Patent landscape analysis shows what areas are potentially rife with third-party patent problems for a given general field of technology. By contrast, what areas remain relatively free of third‐party patents ‐ and possibly are available for appropriation. Useful for

• Track the global activities of competitors and outline their strategies & strengths.
• Monitor R&D trends worldwide.
• Discover the latest technological advances in the area. 
• Spot potential white space in the marketplace.
• Identify new players in the technology space. 
• Identify technologies developed by various players.
• Monitor research collaborations in a technology area.
• Identify potential avenues for mergers/ acquisitions.

What are some of the steps involved with performing Patent Landscape Analysis?

The fundamental idea of patent landscape analysis, sometimes referred to as patent mapping, is to review and organize the patent activity in a technology area. Ideally, you have engaged a patent landscape team consisting of a patent analytics expert and experts from R&D, marketing, competitive intelligence, and legal that are familiar with the technology, area to be analyzed, and have time to commit to the project. Steps involved with creating a successful patent landscape analysis include:

 

1. Establish the purpose of the patent landscape analysis. Why is this patent mapping project being undertaken (i.e., idea generation, ‘white space’ analysis, design around, competitive intelligence, patent filing strategy/patentability, risk management/validity/freedom to operate, monetization, M&A, etc.)?
2. Determine which patent search and analytic software and/or third-party services will perform or assist in the project.
3. Your landscape team will agree on the boundaries of the technology area of focus. It includes considering whether to have product terms, technology alternatives, multiple application areas in the search, and to agree on the goals and outcomes of the patent landscaping project.
4. Determine which countries to include in the search, how far back in time to look, whether to have abandoned patents, family members, equivalent versions of patents, etc.
5. Perform preliminary searches across patents and technical literature and work with the team’s technical and market experts familiar with the technology area to identify a set of relevant keywords, patent class codes, and organizations working in the technical area.
6. Generate an initial training set of documents relevant to the technology area and review those documents to identify additional and refined technology, product, and application areas to categorize the patent information.
7. Use keyword, patent class code, citation mapping, and semantic search strategies. Identify lists of patents that are relevant to each technology, product, and application sub-area.
8. Review and sort the patents within each relevant technology, product, and application sub-category. It can be done through automated means (quick yet less accurate) using keyword and international class code searching. Or manually (time-consuming, yet very accurate) by reviewing Titles, Abstracts, and Claims. Manual review offers the additional benefit of adding meta-data, comments, and value rankings to each result. It will result in a more robust and valuable output. 

Our expert team consists of patent analysts who perform rigorous data mining, data visualization, and data analysis to generate a patent landscape that helps clients identify competitive and technology trends.  

Ingenious e-Brain provides intellectual property research & analytical consulting firm, including customized services in the form of Patent landscape analysis, Patent portfolio analysis, Patent searches (Prior‐art, Patentability, Invalidation, Infringement, and Freedom to Operate), Patent alert and monitoring, Trend analysis, Patent to Product mapping, and patent licensing. Our expertise lies in generating valuable IP intelligence from patent, non‐patent, product, and other technical & competitive information. We provide consistent, high-quality IP research & analytical services in electronics, telecommunications, medical devices, pharmaceutical, biotechnology, life sciences, chemistry, mechanical, and many more. 

 

Why do we need business portfolio analysis?

 

Business Portfolio Analysis is an organizational strategy formulation process based on the philosophy that organizations should make strategy much as they handle investment portfolios. Portfolio analysis is a structured way to analyze the products and services of an association's business portfolio. In the way sound financial investments should be supported and unsound ones discarded, useful organizational activities should be emphasized, and unsound ones deemphasized.

 

Purpose of Portfolio Analysis: 

A viable strategy needs product-market scopes in deciding how strategic objectives will be attained. In a diversified company, one well-received concept of product-market scope is the portfolio approach to an organization's overall strategy. The optimal business portfolio fits the company's strengths perfectly and helps to utilize the most attractive industries or markets. An SBU can either be an entire mid-size company or a division of a big corporation. It typically formulates its business-level strategy and often has separate objectives from the parent company.

 

The aim of portfolio analysis is: 

1) To Analyse: Analyse its present business portfolio and determine which SBUs should receive more or less investment. 

2) To Develop Growth Strategies: Develop a growth strategies for including new products and business in the portfolio. 

3) To Take Decisions Regarding Product Retention: Decide which business or products should no longer be retained.  

 

Advantages of Portfolio Analysis: 

1) Encourages Management for Evaluation: It encourages management to analyze each of the organization's businesses individually and to set objectives and allocate resources for each. 

2) Stimulates Use of Externally Oriented Data: It stimulates externally oriented data to supplement management's intuitive judgment. 

3) Key Areas: These models highlight certain aspects of business that are considered essential to success or failure.

4) Cash Flows: They focus on cash flow requirements of the SBU's and help identify the different cash flow implications and requirements of different business activities. It helps management to carry out its resource allocation function. 

5) Balance Portfolio: They help identify strengths and weaknesses in the portfolio, the gaps to be filled, when a new SBU needs to be added, or when one needs to be removed, and the duplicative businesses in the portfolio. 

6) Diverse Perspective: A multi-business company's diverse activities are analyzed systematically, highlighting enterprise diversity. 

7) Flexible Comparisons: Some matrices are highly flexible in selecting different factors for different industries. This kind of analysis can provide coverage of a vast number of strategically relevant variables. 

 

Why do you need a patent invalidity search?

 An extensive Prior Art Search is performed after patent issuance to examine whether a patent can be proved inaccurate or invalid because the invention was unable to stand true in terms of the basic patentable requirements like novelty, non-obviousness, etc., the time of patent grant. The prior art is evidence that claims that the invention is already known. This search of finding out is referred to as the patent validity or invalidity search. The primary focus of the search is either to check the validity of its enforcement or to invalidate its claims. The search is basically performed because of these three basic reasons:

• To invalidate patent infringement.
• To search for the same patents before any new patent enforcement.
• To check whether the licensor holds an authentic claim to the patent.

An opposition member claiming the invalidity might use these invalidity search results to damage the patent by litigation or applying to the ruling court. When threatened by accusations of patent infringement, prior art-based proof of invalidity art is the initial line of defense. Eminent firms and corporations are eagerly consulting Ingenious e-Brain to discuss all these searches.

Patent Validity Prior Art Search

Before licensing, selling, or buying a patent, a prior art search must be authorized by the client or any relevant search firm to examine the validity of the idea behind the invention and verify that the patent is enforceable. Taking an idea about the background and knowledge about the market before patenting will give the inventor and its invention a powerful negotiating stance.

Patent Invalidity Search

It is an extensive all-out search attack that checks for a complete patent infringement lawsuit. Invalidating a patent may differ according to different territorial regions and national governing laws imposed in that area. The most common claims accepted by the governing laws are the publication of the invention before the priority date of the petition for a patent, sales of the invention, prior public knowledge, or prior public use. In these cases, an exhaustive prior art search will be directed at each of the separate sources of the prior art.

Prior art sources like issued patents, published patent applications, and non-patent literature is the most common sources, although the patent art reservoir is magnificent storage. Physical pictures, examples, brand names, and even sale evidence fall under prior art sources. The search approach differs from one technical subject area to another.

Patent Invalidity Search by Ingenious e-Brain

• We are performing a patent invalidity search for the last 09 years in the market.
• An out-of-box approach that demonstrates a lot more than simple database searching.
• The intensity of the search depends upon the time and budget of the client.
• Searches are done to inspect old product brochures or out-of-date products, locate dukes of resourceful organizations, investigate trade show discovery from the beginning of the history of the technology used, and for a lot more.

Customer Insights: Understand what drives your target market

 

Consumer insights look at the needs of your target market to describe why the market behaves the way it does. These insights can give your business an extensive understanding of consumer behavior, including personal consumer preferences and market trends.

Market research data, such as how many people in your target market would consider buying your product, isn't always sufficient to go on to product development and marketing. Your business also requires to know what drives that data. Consumer marketing insights help you recognize potential customers and make product and marketing decisions that win them over.

Consumer insights and market research

Market research collects data on consumer behavior using research methods such as interviews, focus groups, experiments, and surveys. This research type often generates quantitative and qualitative data, such as market demographics and consumer sentiment.

Market research results are usually either statistical or anecdotal. For instance, you may find that 55% of consumers think it's essential that your business donates to charity. In comparison, 31% think it's somewhat crucial—and some consumers may even recommend a specific charity.

Consumer insights look into market research results to explain the "why" behind a statistic. For example: why do consumers think it's essential for your business to donate to charity? Maybe your brand values align with a certain cause they want you to support. Perhaps they want to feel like they're creating a positive impact when they buy your products. 

How do you get consumer insights?

Every business requires consumer insights and even those with a bare-bones staff and budget can easily create them. Here's how you can find consumer insights in your research data:

1.      Conduct consumer insight research

Businesses with precise data are more likely to develop meaningful insights. Make well-informed conclusions about consumer behavior by diving into your target market's wants, attitudes, and buying behavior with consumer insight research. This type of market research helps you boost correlations between beliefs and buying behaviors.

Although there are many types of consumer insight research, surveys are usually the most versatile way to handle the consumer research questions—and they play a crucial role in more complex research methods such as focus groups and experiments. With surveys, your business can frequently collect data from a representative sample of your market.

There are two fundamental ways to extract consumer behavior insights from your research. You can either straight ask respondents for their insight or establish correlations between data points when your consumer insights research is complete. If you're using the initial method, ask follow-up questions that encourage participants to describe the reasoning behind their buying behavior. Survey logic can support this, as it lets you cover custom questions based on a respondent's previous answers.

2.      Extract consumer behavior insights from research data

Businesses often struggle to handle the information they collect from market research. To develop insights from consumer market research or analytics, you'll require to sift through big data to find the most important data points.

To recognize potential insights, arrange your data so that patterns appear in your participants' buying behavior. To manage big data sets, filter your responses to focus on patterns in smaller segments of your target market. This technique assists you in uncovering micro-trends and correlations and focuses on a more manageable pool of participants.

3.      Build consumer insights data

Consumer insights are only helpful in the hands of the people who know what to do with them. Make a clear impact on your business by sharing your significant consumer insights with co-workers or employees who will gain the most from your research. A shared database or report is an excellent way to make your insights available to anyone at your business who requires them.

New consumer insights help your business remain on top of market shifts, but consumer behavior data from the past can be just as helpful. Past insights are a considerable way to add context to future research questions and benchmark future insights, so hold onto the reports you make—the best consumer insights are those that your business can come back to now and then.

If executed properly, the insights you get from doing more solid customer research will help formulate your marketing strategy, brief your design decisions and guide your future business plans. Customer research should be done constantly as customer needs change or as competitors offer new features. We at Ingenious e-Brain have a wealth of experience measuring customer satisfaction on behalf of our clients, so if you require any assistance in carrying out this type of market research, please get in touch with us at services@iebrain.com.

A Guide To Patent Infringement Analysis

Patent infringement is using a patent for commercialization/Monetization purposes without the patent assignee permission or license. Patent infringement analysis determines the category of patent infringement, such as Literal infringement and Doctrine of equivalents.

 

• Literal infringements: It happens when the accused firm copies the product as claimed in the patent. Two main specifications of literal infringement are: The function of the accused product is similar to the original patent. It is also identical in terms of material and structure.
• The doctrine of equivalents: This includes any partial infringement. If any part of the accused product is accomplishing the same result through the same process, it covers the equivalents' doctrine. 

The steps for a patent infringement analysis are:

1. Describe the claim in a patent thoroughly.
2. Compare the claims and accused products to check for literal infringements.
3. In case of no literal infringement, examine for infringement under the doctrine of equivalents.

The approach is to go into details of the claim as much as possible. In some cases, the complete drawing is similar, and any small part is claimed. The accused product can have multiple similarities with the original patent, but in case it's not violating the claim, It doesn't come under patent infringement.

Aside from literal infringement and the doctrine of equivalents, there are few more types of infringement based on the different violations.

· Direct infringement: If anyone sells, uses, or offers to sell a patent in the U.S.A without any authorization comes under direct infringement.

· Contributory infringement: Duplicating a part from a patented invention and then use or sell it comes under this infringement category.

· Process patent infringement: Importing any innovation in the U.S without the authority of the patent owner comes under process patent infringement.

· Litigation process after patent infringement analysis

Once the patent infringement analysis is done, courts have a two-step process to find out the result.

1. Claim construction 
2. The court governs whether the accused product infringes on the authentic patent.

Claim construction is the scenario when the court describes the claims made in the patent. During this process, the precise meaning of the term is considered. Although, it can be changed if the patent owner gave a different meaning to the term. Large firms focus on developing a patent claim construction to establish their position on the legal front.

The court judges the product depend on functionality. Any part in the claim is considered as a method to complete a function. It finishes the opportunity of the claim. If a meaning for a technical word is not clear, the court considers the meaning specified by experts or textbooks. In conclusion, claim construction is entirely under the court. However, parties can have a jury trial interrogate the court's interpretation of patent infringement. Moreover, there are specific ways to defend a patent infringement lawsuit.

Want to conduct a patent infringement analysis?

Ingenious e-Brain has more than 9 years of experience in the IP field. Our team covers possibly every technical domain. We go through every database to deliver accurate results. Also, the clients can examine the status of the work at any stage of the process. Most importantly, 100 % customer satisfaction is our top priority.

To know more, visit our service page: https://www.iebrain.com/services/ip-intelligence/infringement-analysis/.

How Is AI Relevant For Due Diligence?

 

There is a constant apprehension that artificial intelligence will automate professional fields and create mass redundancies sweeping through the legal sectors since last few years ago. While those fears are still unfounded. AI technology is beginning to change the due diligence process.

Today, artificial intelligence. (AI) in due diligence process has become an integral part of the industry. Now it is time to separate its hype from reality and observe how top tier lawyers are employ AI-based tools for day-to-day processes. It can also be used to examine the challenges and benefits of using such software and have a look at the future of the due diligence process.

The adoption of AI for the legal industry has not eliminated the need for human insight. It helps law practitioners unleash tremendous potential by automating repetitive tasks and allowing them to spend more time on other higher-value tasks.

Due Diligence in the New Era

Machine learning, a sub-division of artificial intelligence (AI) is advancing to change the very nature of regulatory due diligence and the due diligence team’s capabilities. Advancements enable the teams to sort through vast information faster, relieve skilled labor, save time, cut costs, and improve due diligence quality and data coverage.

AI is full of potential to improve due diligence programs’ efficiency and effectiveness in the coming years. To better understand this potential, we also need to realize the limits of this technology.

Structuring Due Diligence Using AI

To understand the use of AI on due diligence, it’s helpful to review the general due diligence research process, which is split into two main phases:

1.       1. Information discovery

2.       2. Information synthesis

During information discovery, the researcher uncovers information using various sources, such as Google, litigation repositories, and corporate registries. They further qualify knowledge by determining how applicable it is for the subject and the relevance of AI to the due diligence. For instance, the researcher spends time to make sure the findings aren’t referring to another person with the same name as the due diligence subject to satisfy the first qualification. Simultaneously, suppose the information concerns the correct subject. In that case, the researcher determines whether the content is relevant to the purpose, typically determining if the information is relevant to a risk assessment or not.

Throughout this process, researchers even need to conduct information synthesis. During this process, the researcher sorts the information gathered during the discovery stage and makes sense. The researcher decides how the data fits into the case, makes connections between findings, and distills information that fits into the context. Essentially, the researcher compresses data in a more digestible form for the consumer in the research report. Information discovery is also an iterative cycle for synthesizing critical information; this may lead the researcher to think of new investigation angles, leading to a new iteration of information discovery.

Clustering of Results

A common and time-consuming obstacle that a due diligence researcher faces are determining what information is and is not attached to a proper interest subject. For instance, when specialists research an issue with a common name, it is time-consuming to match information with the correct individual without dealing with mistaken identity cases positively. Machine learning now uses a process called result clustering to automatically determine whether the information pertains to the subject of interest, resolving the subject’s identity, as more and more information, is parsed and linked to the actual issue.

Notably, the clustering process takes seconds, saving the researcher’s hours of sifting through results one by one. It also lower downs the likelihood of human error accompanying cognitive fatigue using limited search result previews to determine the applicability of the work to the subject of interest, which shows only a fraction of the product’s available information.

Learning to Rank

Learning to Rank (LTR) algorithms sort through results and re-rank them based on due diligence researchers’ factors after being trained on examples of products that researchers care about. For instance, in a hypothetical Company X, LTR algorithms may show the researcher X company’s court cases fir rather than having the subject’s most popular blog posts flooding the search pages. For this, AI can help to push research-relevant content on top of results. Using this, researchers can quickly review important information and avoid being weighed down by more consumer-focused content.

Result Classification

Several classification models can filter and organize relevant content by labeling training data and supervising learning techniques. Here the program learns from the activities of a human. These techniques train a model to uncover generalized patterns in textual examples labeled against one or more categories. A model rapidly parses through thousands of unseen examples and quantitatively predicts the results falling into different types after being introduced.

Result classification enables due diligence researchers to focus only and only on the results falling into the categories they’re most interested in. It feeds researchers’ results that stand out as ambiguous or can fall into overlapping categories. This way, researchers can disqualify highly irrelevant content and review works that remain ambiguous to the model.

Emerging AI capabilities can free up compliance and research experts through due diligence and high-level risk management activities. However, organizations still have dedicated due diligence teams and risk assessment strategies that drive effective risk management processes. To maximize AI’s benefits, it’s essential to understand what technology precisely fits your program and thereby choose the right provider.

Why is Technology Benchmarking Important for Your Business?

 Technology benchmarking incorporates measures of the performance of your business against your competitor in the same industry domain. Comparing the business from your competitors is crucial to improving your understanding of business potential and performance.

The technology benchmarking offers insight into how your business is performing, enabling you to discover what areas of improvement are required while developing a plan to accomplish those improvements.

Technology benchmarking is a tool for business that helps to identify the opportunities for improvements, like:

· Recognizing and prioritizing the main areas of opportunity.

· Understand the need of your customers better.

· Recognizing your weakness and strength.

· Setting up performance and goals expectations.

· Tracking the performance and changing the managing effectively.

· Understanding your competitor’s perspective to be more competitive.

Primary Classifications of Benchmarking

Certain kinds of benchmarking can be classified into three main categories — internal, strategic, and competitive.

1. Internal benchmarking is used when an organization already has established and proven best practices and basically needs to share them. Again, depending on the company's size, it may be large enough to address a broad range of performance (i.e., cycle time for opening new accounts in branches coast to coast). Internal benchmarking also may be necessary if comparable industries are not readily available.

2. Competitive benchmarking is used when a zx wants to evaluate its position within its industry. Moreover, competitive benchmarking is used when a company needs to recognize industry leadership performance targets.

3. Strategic benchmarking is used when identifying and analyzing world-class performance. This benchmarking is used most when a company needs to go outside of its industry.

Six steps to successful benchmarking

Use the following steps to practically benchmark your business against your competitors:

1. Competitive Landscape — Check what all similar technologies or solutions are present and the solutions under development through technology landscape or scouting services.

2. Identify Key Areas of Innovations and Development — From the technology landscape or scouting report, you can analyze the areas or technical fields with the most innovations and developments and areas for improvement. Identify effective techniques used by your competitors and areas in which their business is performing better.

3. Finalize Benchmarking Parameters — Benchmarking parameters should cover all the aspects of the scale of benchmarking such as intellectual property (IP) protection, key advancements or innovations, technical features, unique selling propositions, consumer or customer reviews, technical reviews from several secondary sources, number of citations over publications and technology scoring.

4. Allocating Weightage to Benchmarking Parameters — After finalizing benchmarking parameters, it is essential to weigh all the parameters according to the value they should be having in the total score or rank. Make sure you give required weightage to technical parameters, business parameters, and IP parameters to benchmark required solutions or technologies in a right way

5. Scoring and Evaluation — Scoring and evaluation involves some mathematical calculations and models depending upon the gathered information or required output which helps you to provide rank or score to each solution or technology

6. Planning and Taking Better Strategic Decisions — Benchmarking results can help you make better strategic decisions, be ahead of your competitors, know consumer demands and how the industry is addressing those, know the potential of competitors, and analyze the future competition.