Scion Analytics Created Jobs And Expanded As Part Of Tampa Bay Tech Hub

Scion Analytics Created Jobs And Expanded As Part Of Tampa Bay Tech Hub

In every city across America, the economic recovery after the pandemic looks different. For many industries that consider Tampa Bay their home, it has been a welcome return to opening doors to customers and scaling operations. It is due to Tampa Bay’s overall competitiveness to thrive and innovate that the city solidified as a new tech hub outside Silicon Valley.

As more innovative tech solutions originate in Tampa Bay, VCs, startups, incubators, and accelerators improve the economy. These companies contribute to a fast-paced job-creating engine that attracts world-class talent to the area. One of such companies is Scion Analytics that is expanding and adding value to the community.

Recently, Scion Analytics celebrated its growing presence in the community. Tom Lipscomb, Executive Vice President and Founder of Atebion said, “It was the continuous drive for advanced innovation that led to the merger of Atebion LLC to form Scion Analytics last year.” Scion Analytics offers enterprises the Content Analytics Platform (CAP). It uses Artificial Intelligence (AI) and Natural Language Processing (NLP) to read and analyze unstructured data, data they didn’t even know they had.

Atebion started as an idea for a solution to automate the proposal process in the government contracting industry. As it merged to Scion Analytics, it added more than 20 new tech jobs and found innovative uses for unstructured data in the commercial sector. Unique, propriety technologies based on AI and NLP changed the way enterprises work with content. It allowed Scion Analytics to achieve what few companies can do – bridge the gap between government contracting and the commercial sector.

Scion Analytics CEO, James R. Eddy, reflected on the anniversary, “A year ago today we completed the merger into Scion Analytics with a company that has a legacy of more than a decade. There were many challenges ahead of us. Some we knew were coming and some we didn’t. We were starting in the middle of the pandemic. We had to ensure we continued to provide our current customers with industry-leading service. New product strategies around Content Analytics, AI, and Natural Language Processing had to be devised and executed…and we needed to greatly expand our team to execute those strategies. We’re also aggressively expanding into commercial industries.”

As a result, Scion Analytics focused on service delivery which resulted in 2x the business. Scion Analytics encourages employees to be directly involved in innovation. The mission is to build best-of-the-best team with diverse talent and a culture of curiosity. For Scion Analytics staff to contribute to the excitement and fast pace of the Tampa Bay tech scene. Eddy commented, “I’m proud of how our team grew together, responding to these challenges and growing our business. Our future looks even more exciting as we added a new Development Team that is entirely focused on innovation and a Consulting Team to assist our enterprise customers in leveraging our platform and expertise. Some very interesting news is coming so stay tuned.”

As Tampa Bay transforms into a world-class tech hub, it is companies like Scion Analytics that are setting the tone. While enterprise clients explore the possibilities of the technology, it is local talent that imagines what these technologies can do.

The Benefits of Cloud Transformation

The Benefits of Cloud Transformation

The digital future is here, and it is glorious. So, are businesses prepared for the demands of tomorrow?

This decade has seen a massive change in the way businesses operate with the transition from analog to digital and subsequently the optimization of digital assets. This can be likened to a new radical digital world. The concept of digital transformation shifted the traditional business paradigm with the adoption of digital technology. A change that has revolutionized business operations and redefined the value proposition to customers.

The new world is one where traditional infrastructure or legacy has become outdated forcing businesses to adapt or be left behind in analog obsolescence. To innovate, businesses need to undergo a successful cloud transformation. From small businesses to enterprises, businesses across industries are thriving due to cloud transformation.

What Is Cloud Transformation

Cloud Transformation is the process of moving work to the cloud such as apps, data, and software programs or an entire infrastructure as it supports business objectives. The transition to the cloud places new external and internal demands on businesses. Internally, employees are empowered to work from anywhere, anytime, and on any device. During the COVID-19 pandemic, a generation of workers went remote embracing the flexibility and seamless of work from home (WFH). Externally, massive amounts of information are being managed for clients and prospects on the cloud. These are fundamental IT requirements of a cloud transformation that requires a considerable investment to be successful. Because of the high cost of entry, cloud transformation may be cost-prohibitive for some businesses. Some businesses end up looking for a more cost-effective IT solution.

Leverages Service Providers

One of the benefits of cloud transformation is the ability to leverage cloud service providers. It enables the business to make a smaller initial investment while modernizing the IT infrastructure. Companies that transition to the cloud become more agile and innovative with lower operating costs and higher levels of service.

IT Efficiency

Another benefit of cloud transformation is increased efficiency in the delivery of IT. For a business in the cloud, the focus shifts from day-to-day operations managing infrastructure to mission-critical business results. It gives employees freedom and resources to innovate. As a result, operational gains are quickly made that would have been impossible in an on-prem environment.

Improved Customer Service

Better service delivery is another benefit of cloud transformation. It pushes the business to improve customer service, an important differentiator in the marketplace. It also forces the business to have a better plan for the performance and security of data that goes beyond cloud service providers. It is the responsibility of the business to find support that manages the quality of each new cloud service and align it with the overall cloud initiative and strategy.

Conclusion

The new radical digital world is here, and it has forever changed businesses. To stay competitive in the marketplace, businesses need to modernize IT infrastructure by migrating to the cloud. Cloud transformation is a powerful tool that transforms a business’ operational efficiency, profitability, and customer service. A business that moves to the cloud is a business that becomes agile and innovative. One that is confident in its ability to thrive and digitize operations. The cloud is a tool that has altered the business paradigm for the future. It is a matter of time to see how businesses measure up to the new IT standard.

What Is Government Contracting?

What Is Government Contracting?

Government contracting is when a civilian business product or service provider supplies the requested needs of the United States government, which can be a federal, state, or local agency. In the commercial world, when a business needs a product or service to provide for public demand, that business invites requests for any company’s supply proposal. A capable company then submits a proposal to meet that business need adequately and affordably. The same economic exchange takes place in the government arena, where civilian companies are vendors to the US government agencies’ business needs for various products and services. The largest customer in the world is the US government.

Fundamentals Of Government Contracting

· Fair competition, where the government agencies’ request for proposals are open to all public contractors.

· The proposal assessments and bidding awards are fair and transparent to all competing vendors.

· Fair pricing is sought from all potential vendors.

· Pricing is according to the goods and services requested.

· Full product compliance is necessary according to the government agencies’ strict requirements.

· Full lawful compliance from both the government agencies and the contractors according to the many Federal Acquisition Regulations (FAR) or the Defense Federal Acquisition Regulations Supplement (DFARS). Individual companies might also have their own regulations.

Government Contracting Examples

Fixed-Price Contracts

Fixed-Priced Contracts require the contractors to bid with predetermined pricing, and very little cost adjustment is expected but some may be included in the original contract. This type is the most common with state and local government agencies.

Cost-Reimbursement

Cost-Reimbursement and Cost-Plus Contracts are types of contracts where contractors estimate the cost beforehand to establish an agreed-upon ceiling of reimbursement for contingencies. These types of contracts are used when uncertainties cannot be foreseen. These would be used by the Department of Defense where the cost of a war cannot be predicted, or the National Weather Service where storm monitoring cannot be predicted.

Time And Materials Contracts

Time and Materials Contracts are like the others and makes the government bear most of the risk of a contract. This type is used because it is not possible to accurately predict the cost of a project. The government agency basically pays the contractor an hourly wage.

Indefinite Delivery/ Indefinite Quality (IDIQ)

Indefinite Delivery/ Indefinite Quality (IDIQ) Contracts are often used for supplemental or amendment reasons to other contracts. These allow flexibility about supplies or other aspects of a project. The IDIQ type is a main contract that permits the government agency to select various sub-tasks under the umbrella IDIQ contract that will be awarded to the same group of bid-winners in the future. This type allows the streamlining of awarding contracts in the event of a national emergency.

Government Contracting Benefits

The main benefits of government contracting are that they help the small businesses by providing commercial opportunities for them rather than only large businesses. They ensure the discovery of new ideas that small businesses usually birth. They promote the economic growth and new job opportunities that small businesses foster. They encourage the employment of the disadvantaged social classes.

Conclusion

The US government is the largest customer in the world and has generous buying power for successful contract winners. Contracting with a government agency, whether at the federal, state, or local levels, can be the key for growth and enrichment for both small businesses and enterprises alike. A strong and compliant proposal for a government agency bid can be ensured by using the Content Analytics Platform (CAP), the software application that was developed by Scion Analytics, specifically for ensuring confidential document data management and contract winning.

Benefits Of Automation in IT

Benefits Of Automation in IT

Automation in Information Technology (IT) means the automating of data calculations, algorithms, and processes required for digital technology needs, which in turn serves other needs required in various industries. In a sense, to speak about automation in IT is to speak redundantly because the very principle of information technology is automation itself. With the clever manipulation of a binary system, calculations and processes are automated with inhuman efficiency and speed. This is because the underlying actions of calculations, arrangements, discoveries, and other processes are themselves first being done with amazing ease, speed, and reliability. These first actions are the results deriving from the technologies of Natural Language Processing (NLP) and Artificial Intelligence (AI). Common business tasks can be accomplished with the largest parts being automatically performed.

Automated Reasoning Technology

Every high-tech industry has products or services that are suited for human consumption. These commodities are sensible for our existence. When qualified people provide these products or services in some small measure, without the advantage of IT assisting the many intermediate processes, then the overall output of the accomplished work may be of good quality but will inevitably be very limited. But the abilities of IT use such basic tools as calculation, computation, arranging, and sorting. These IT tools increase output exponentially. All these abilities are done by underlying human reasoning design. Natural Language Processing (NLP) and Artificial Intelligence (AI) are two other technological advantages that help with data management needs by the associative reasoning. These learn, in a sense, of what people are saying online, and then leveraging that data for business and other purposes.

Automated Document Data Management

Important business documents that need to be perused or analyzed, such as proposals, contracts, and resumes, require much time and care when being done by individuals themselves. This method will be slow and possibly inaccurate. The larger the documents, such as request for proposals (RFPs) and business proposals, legal contracts and government bills, the more cumbersome to be parsed. They demand many personnel and manhours of labor to accurately absorb and analyze the data content for successful response or manipulation. But imagine what you could do if you had a single application that could comprehensively, accurately, and speedily analyze content data automatically with a few keystrokes? Such a software tool would effectively demonstrate the key benefit of automation in IT.

Conclusion

There are many benefits of automation within Information Technology (IT) itself. With IT, we have the assistance of efficient robots in the workforce, which in turn provides the many benefits of accurate products, economic use of resources, tireless output, a safer workplace for personnel, lower overhead costs, and affordable products and services for the consumers. The remarkable benefit of automation provided by, and due to, IT itself is what the Content Analytics Platform (CAP), developed by Scion Analytics, is about. The application uses such key technologies as Natural Language Processing (NLP) and Artificial Intelligence (AI) to quickly analyze document data, and structures that data so that it can be leveraged for successful business accomplishments

Request for Bid Vs. Request for Proposal

Request for Bid Vs. Request for Proposal

Request for Bids, or Invitation to Bid (ITB), or Sealed Bid and Request for Proposals (RFP) are two types of federal government requests for civilian contractors to perform construction work or provide goods and services.

What Is A Request for Bid?

A Request for Bid is announced by the federal government for all interested and qualified contractors. It is intended as an unbiased call. It is a straightforward ask for work to be done at the lowest possible price. It promotes fairness in the awarding of the contract. The bids are submitted in sealed envelopes. The federal government calls with Requests for Bids when the requirement is over $100,000.

What Is A Request for Proposals (RFP)?

A Request for Proposals (RFP) is announced by the federal government for all interested contractors. In awarding contracts, the government considers expertise as well as low pricing. By law, government agencies are required to make public calls for services to prevent unfair commercial favoritism. This public invitation stimulates competition. RFPs demand detailed specifications, more skill, cost-effectiveness, and strict compliance. The contractors submit a proposal describing what they can provide and at what price for the requesting government agency.

Similarities

The similarities of these two types of requests are they both invite any qualified contractor that can supply what is needed in a manner that is adequate, fair, cost-effective, and unbiased. Both types share problems that can be encountered. They will tempt vendors to bid low to win contracts, but then the vendors can lose financial gain in the end due to unforeseen costs because they priced their services too low. This in turn can cause project delays, bankruptcy, and litigation.

Differences

The differences between these two types of requests are that the Request for Bids does not demand projected cost and completion promises but the Requests for Proposals does consider these estimates. For Requests for Bids, the costs can make a bidder to stand out to the government agency. For Requests for Proposals (RFP), the expertise, the costs, and the project completion promises will attract the best contractor proposal. The Request for Bids type is used for most government contracts. These draw the lowest bidder and promote a fair opportunity for all vendors. The Request for Proposals (RFP) are more demanding concerning vendor skill, cost-efficiency, and complex requirements compliance.

Conclusion

Both types of federal government requests for contractual supply are great opportunities for vendors to gain financially. All competitors have an equal chance to win the contract. Small businesses and new ideas are encouraged to apply for the projects. They demand appealing proposals to win the government contracts. Appealing bids and proposals must be adequate and compliant according to the project requisition. A robust software application that can analyze a written proposal would prove useful for successful bidding. The Content Analytics Platform (CAP), developed by Scion Analytics, can effectively check a proposal document’s data content for the full compliance that gains the award of a contract

A Glimpse Into The Future Of Artificial Intelligence

A Glimpse Into The Future Of Artificial Intelligence

Rapid Progress In Artificial Intelligence

Innovation in the field of artificial intelligence (AI) is rapid. Developments that were new and exciting 10 years ago such as deep learning are now the status quo when it comes to best practices. At the intersection of science and technology, AI practitioners are determined to make progress and change the way society works.

Just a few years from now, modern AI will look different. Some methods used today will be obsolete and new ideas will redefine the field. Research that is in nascent stages today will come to define the art of the possible for tomorrow.

Future Developments In AI

1. Unsupervised Learning

These days, the current paradigm in AI is supervised learning. Supervised learning involves human “supervisors” curating data sets with predefined categories for AI models. The human element of supervised learning is expensive and time consuming. Manually labeling data points creates a bottleneck in the process. It also places predefined limitations on AI on concepts and categories. AI can only operate on the given information and relationships in a data set given by supervised algorithms. The future of AI includes unsupervised learning which removes human guidance from the process. The premise of unsupervised learning is that it would operate much like human cognition does by exploring the world. A system forms an understanding of the environment from observing patterns and relationships in parts of the environment. Unsupervised learning is “learning everything from everything else” and it already has had transformative results in Natural Language Processing (NLP) and holds the key to developing human-level AI.

2. Federated Learning

Data is the currency of AI. This makes data privacy an integral issue in the successful execution of AI models. Data privacy is regulated by various laws and regulations. Therefore, the practice of federated learning is focused on enabling AI models to learn from a diverse set of datasets without compromising privacy. For modern AI models, the traditional practice is to gather datasets in one place such as the cloud to train the model on the data. This is nota practical or efficient approach in today’s data environment which has security and privacy regulations about creating a central data repository. Federated learning was first studied by researchers at Google and has gained significant interest in the field. In application, federated learning has made tremendous gains in fields like healthcare. Healthcare is a highly regulated industry with laws like HIPAA guarding sensitive patient information. The use of federated learning has enabled AI practitioners to develop lifesaving AI tools without privacy breaches.

3. Nuance In AI

In the last decade, we have witnessed the golden age of AI. In the arena of work, AI is defining the future of what is possible and what can be imagined when it comes to automation. NLP is also having a moment with advancements in parallelization. Parallelization occurs when all tokens in a sequence of text are analyzed at once rather than sequentially. This improves the accuracy and speed of AI models. Furthermore, even the US military has made advancements in AI by developing algorithms which can detect sarcasm in text. The military uses this capability to analyze the intent and content of social media posts in countries of interest. A new wave of AI capabilities is being worked on including ambiguities, colloquialism, and the evolution of language.

Conclusion

The future of AI is here, and it looks promising for advancements in supervised learning, federated learning, and nuance of language in NLP practices.

Benefits Of Sentiment Analysis

Benefits Of Sentiment Analysis

What Is Sentiment Analysis

Sentiment analysis, also known as opinion mining or emotional AI, is a way of knowing the thoughts or feelings of people regarding any topic expressed on the Internet. It means analyzing people’s online textual comments regarding a certain matter, service, or product to gather the essential mood they feel. Sentiment analysis uses the digital technologies of Natural Language Processing (NLP) or Artificial Intelligence (AI). This process is beneficial especially for various business products and services but can serve any area of life. In business, it is valuable for marketing, e-commerce, advertising. It can also be useful in politics or any global research need.

Benefit For Business Information

Perhaps the primary use for sentiment analysis is providing businesses the ability to be aware of how their products or services are appreciated by the consumers. This lets companies know how to improve or limit their offerings. People naturally want to see that their efforts at helping in some way is useful. Sentiment analysis is a digital way for a company to assess this.

Source For Customer Feedback

Every high-quality business cares what consumers think about their purchased products or services. Sentiment analysis can gather these publicly expressed attitudes through the canvassing of social media, blogs, articles, reviews, and discussion forums. Using the technologies of NLP and AI, general customer feedback can be known.

Monitor For Market Buzz

Vast amounts of online textual data is readily available for sentiment analysis to help see market interests or trends regarding products or services. These can be new or old, niche or ordinary. In a sense, online textual data is like scattered commodities that just need to be picked up by the savvy marketer. When the public express what they like or dislike, then a company can know what will be successful or not.

Means For Crisis Prevention

Most companies care about their brand’s quality. When consumers are dissatisfied with a product or service, they feel compelled to mention these opinions through social media, websites, or product reviews. These sentiments can be detected in real-time to prevent large-scale damaging impressions. If monitored well, it also helps with real-time customer service in the effort to prevent widespread public disapproval. Not only in the marketplace but also in national or global political affairs can sentiment analysis be useful for preventing bad public persona or threats of violence.

Conclusion

Sentiment analysis is becoming important in the business of marketing, e-commerce, advertising, and even politics, because it is a process of analyzing the opinions and attitudes of people anywhere technology is available. Things which would not be possible without the digital technologies of NLP and AI, which uses algorithms and rules to learn how people speak and express their opinions about anything posted through any digital medium, such as social media, websites, blogs, and discussion forums. The Content Analytics Platform (CAP), developed by Scion Analytics, is a robust software application that uses these technological advances for companies to leverage invaluable structured data.

Business Development Automation

Business Development Automation

Automation has enabled businesses across industries to scale and explore new opportunities faster. According to research, 80% of leading companies have implemented automation for marketing. This boom in automation has had significant implications on the labor force and the way business is done. Research has found that by 2030, up to 800 million global workers could lose their jobs to automation. Workers being replaced by robots shifts the dynamics of the workplace and creates new challenges and opportunities for the business. Every industry is adjusting differently to automation and how it can augment productivity. For a dynamic industry, such as business development, the adoption of automation means the outsourcing of repetitive tasks and paperwork to robots for humans to focus on developing new business.

What Is Business Development Automation

In business development, automation is used to enhance the partnership between humans and computers. Computer algorithms are designed to take over mundane work from humans. This allows business development (BD) professionals to focus on higher-level tasks and duties that yield the most profit. For example, BD pros could use machine learning (ML) to parse and filter contact lists to identify the most active leads and compile profiles. This allows the BD pro to contact leads with highest pay off and become more efficient with sales scripts. As intelligent automation is becoming more accepted in the workplace, BD as an industry is developing best practices to coach human employees.

Business Development Automation Examples

Email Automation

Some examples of the way automation transforms BD is enabling instant automatic responses from email. Research has found that if it takes even 30 minutes to make a contact or reply to queries, it reduces the probability of converting a lead by 21 times. By automating emails, a business acknowledges customer queries instantly and can deliver better customer service.

Chat Bots

Another example of automation at work is AI solutions for customer services. Research has found that 58% of B2B organizations use AI solutions such as chatbots on their website. Chatbots are used as the first line of defense to resolve complaints and questions from customers before being handed off to a human customer service agent. Customer service is an integral part of the sales cycle, and its improvement enhances the opportunities to win better business for BD.

Business Development Automation Benefits

Automation improves processes in the BD industry as it does for many industries in the marketplace. Because BD is heavily reliant on emotional intelligence and creative problem solving, it presents an interesting use case for automation. While some disruption of BD is expected by machines in entry-level positions such as analysts. The foundation of BD work is unlikely to be usurped by machines. It deals significantly with negotiation, improvisation, and empathy.

Conclusion

These are intricate and nuanced human skills that are not easily replaced by machine algorithms. Perhaps, the best of both worlds can exist for the future of the BD industry. It is resilient enough to not be taken over by automation yet progressive enough to incorporate automation practices to be more successful.

Text Analytics For Finance

Text Analytics For Finance

What makes an industry successful? The ability and the willingness to innovate with the times and customer demands to deliver better services and products to the customers. Finance is one of those industries. Highly regulated and complex, finance has leaned into new technologies to deliver a better customer experience and embrace opportunities. Text analytics technologies have been a natural fit for finance as unstructured data became accessible to the industry. 

These days, the financial sector can derive high-quality structured data from unstructured text. Unstructured data from sources such as social media, email, instant messaging, and online forums are being used for data-driven insights. Processes like sentiment analysis are being leveraged for financial applications. The predictive power of sentiment scores is a game changer for financial professionals.

What Is Text Analytics

Text analytics is the process of converting large sets of unstructured text into quantitative data. Finance professionals and data scientists can mine unstructured data to uncover insights, trends, and patterns. This enables businesses to compile a story behind the numbers to make more precise decisions.

Unstructured data is the new currency for the digital age. Businesses had leveraged structured data for years. Data that was organized and easy to mine provided limited insight into what made customers tick. The opportunity to mine unstructured data changed all that. In an organization, 80-90% of data is unstructured. Though, free form and difficult to access, unstructured data provides a wealth of data to fuel text analytics tools.

Text Analytics Examples

The financial sector industry is ahead of the trend when it comes to utilizing text analytics to gain insight. Here are some examples:

1. Investors

Good investment practices can be a profitable venture in finance. Investors seeking a more data-driven approach lean on text analytics for insights.

2. Portfolio Managers

 Use text analytics to cut through the noise to recognize important highlights in investor notes, blogs, and news.

3. Data Scientists

 Fuel trading models and investment strategies with structured data that has been derived from unstructured text content.

4. Compliance And Risk Managers

 Leverage text analytics tools to increase compliance rates and get alerted to relevant internal conversations.

Benefits Of Text Analytics For Finance

The financial sector is a $35.5 billion market that invests heavily in the information industry. Finance accounts for 9.8% of the entire information industry. The investment pays off as text analytics tools yield tremendous benefits for financial professionals. Text analytics practices such as sentiment analysis take client’s everyday content such as emails, social media, and personal information convert it into forward-looking insights. For the finance industry, text analytics provides the opportunity to hyper-personalize the customer experience and improve the bottom line.

Conclusion

Unstructured data has redefined the way businesses process information. It has been the catalyst for innovation for many industries including financial services. From investors to compliance and risk managers, text analytics tools such as the Content Analytics Platform (CAP) from Scion Analytics enable a more successful and personal customer experience.

What Is Dictionary Weighted Analysis

What Is Dictionary Weighted Analysis

Dictionary weighted analysis, a capability has been used to assign weight to content for deeper analysis. As automation becomes more sophisticated so do the use cases. For example, HR has leveraged the capability of Dictionary Weighted Analysis to compare content differences between documents by assigning weights. Prior to automation, a collection of resumes took hours of HR human capital to review and compare resumes to find the best candidate. By creating a dictionary and assigning weight values to each term, HR automates the resume process and saves time. As a result, the best candidate is selected in an efficient manner.

The future of business is dictated by advancements in automation as it enhances human intelligence in different sectors of work. Technologies like Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML) have redefined the way business is conducted by outsourcing redundant tasks to machines. As a result, more human ingenuity has been allotted to exploration and innovation.

Using Dictionary Weighted Analysis For Resume Analysis

Here is a detailed example of how the Content Analytics Platform (CAP) can be used for resume analysis. If you had 20 people apply for a project manager job, you can use CAP to rate the batch of resumes. Traditionally, recruiters looked at individual resumes to determine whether certain keywords integral to the job description were present. After highlighting keywords, the recruiters then scheduled an interview based on eligible resumes.

The Dictionary Weighted Analysis of the CAP can save your HR department the half a day it would take to go through 20 resumes manually. It saves the time of highlighting the words, keeping track of the number of times the word appears, and figuring out which words are important in each resume. If you set up the CAP with a dictionary that had not only keywords but synonyms and assign weights to the keywords, the CAP can analyze 20 resumes in 30 seconds.

The CAP would show you resumes in order of the number of times the words you were interested in appeared in the resume and show you the

same rank taking assigned weight into consideration. For example, hiring for a project manager, a “PMP” and project management professional can be set up as equal synonyms and given a high weight of 1.0. So, if you were looking at resumes, in order of importance you would look for a project manager who had a “PMP” as a “must have” for the job. Then, you could assign a much lower weight of .5 for a “nice to haves” keyword such as “scrum” or “agile certification”. Also, you could also set up CSM (certified scrum master) as a synonym for an agile certified practitioner (ACP). Similarly, a “nice to have” keyword in a project manager resume such as – “business analysis” could have “BA” with an assigned weight of .2.

(Suggest using Janson’s updated Resume Comparison template containing bar charts as an image in this blog).

Why Does Dictionary Weighted Analysis Matter?

Dictionary Weighted Analysis helps businesses make smart decisions. Smart decisions are more precise due to being data driven rather than based on guesswork. Dictionary Weighted Analysis provides the ability to capture important and critical textual content in unstructured data. Unstructured data was previously inaccessible to businesses because it was difficult to access and mine. In the HR example, Dictionary Weighted Analysis removes human error and bias in analyzing resumes. It is also sensitive to how important certain terms are to the business. Weights range from 0 to 1.0, at the hundredth level (e.g., .55). Typically, the greater weight, the higher the importance. This can be used in either a positive or negative aspect. A positive aspect is scanning resumes for skills with the “must-haves” having the weight of 1.0, while the “nice-to-haves” are .25. The negative is the inverse of the positive, such as identifying high and low risks.

Conclusion

Scion Analytics empowers users of the Content Analytics Platform (CAP) to imagine what they can do with the platform. Scion Analytics’ Dictionary Weighted Analysis creates flexible dictionaries and provides deeper analysis for content. The capabilities of the platform can be quickly customized to fit business needs. A common use case is the Bid/No Bid requirement analysis, determining the requirements to a company’s capability and identifying risks associated with these requirements. Also, Dictionary Weighted Analysis can be used to identify risks in an agreement, contract, and Request for Proposal (RFP). It could also be used to identify

words and phrases that should not be used in company documents such as proposals.

Our users have developed other use cases for using weighted terms that we never imagined.

If the future of work belongs to intelligent automation, it is content analytics tools like the CAP and capabilities like Dictionary Weighted Analysis that are examples of new opportunities to come.