Patent for Automated Form Generation and Analysis

Patent Title: Automated Form Generation and Analysis

USPTO Pantent: US10956664B2

Patent Document: https://patents.google.com/patent/US10956664B2/en

Grant Date: 23-03-2021

Expiration Date: 26-08-2037

Inventors: Hemant Kakkad, Kinnar Shashikant Galani, Nitin Kumar Gupta

TL;DR:

This article demonstrates the journey of converting an idea into a patent worthy solution.

1. I worked at Accenture's PSCOE from 2015-2018, focusing on blockchain and data privacy solutions for public service organisations.

2. Identified a market need for GDPR compliance solutions and developed an Automated Form Generation and Analysis system.

3. Created an MVP in 3 months that assessed data privacy risks at industry, organization, and peer comparison levels.

4. Key features included form analysis, scoring systems, recommendations, and benchmarking.

5. Gathered feedback through internal roadshows, client visits, and newsletter articles.

6. Filed a patent application, which was granted in 2021 (5 years after initial filing).

7. Gained valuable experience in problem identification, MVP development, product roadmapping, and pitching to executives.

8. The project provided entrepreneurial experience within a large organisation setting.

About the Patent:

During the years of June 2015- Jan 2018, I was working with the Public Service Center of Innovation and Excellence (PSCOE) at Accenture. The main mission of PSCOIE was to identify and solve challenges faced by the global public service organisations and solve it using emerging technology. The PSCOE was working with clients like Metropolitan Police UK, Singapore Customs, UK Postal Department, UK Pensions Department and others.

Background:

Back in 2015-18, I was working with the PSCOE as a Product Owner creating a portfolio of software assets related to blockchain and data privacy. Two major reasons why we were focused on blockchain and data privacy:

1. in 2015-16, Bitcoin was becoming mainstream which also drove everyone's attention to the underlying technology of a public distributed ledger system called the blockchain.

2. Also, in 2016- European Union had announced that they are coming up a new stronger data privacy regulation called as the General Data Protection Regulation (GDPR). This is where public service organisations were exploring ways to assess and control privacy risks during data collection, storage and sharing with other internal and external entities. GDPR also levied heavy penalties on orgs who were processing data of the EU permanent and temporary citizens.

This problem statement was very common across multiple conversations that my team used to have with CXOs from the partner public service organisations. We could sense that there was an immediate unmet market need for a solution that could help organisations achieve their GDPR compliance goals. This laid the foundation of Automated Form Generation and Analysis.

Approach:

We started conducting multiple user calls with relevant stakeholders from the target public service organisations. We also started analysing the data privacy regulations across a few key geographies including the new GDPR regulation. This activity helped us get a closer view at the common pillars across the data privacy requirements of the organisations. We also performed analysis on the existing data privacy solutions to understand the gaps.

The roadmap:

We had come up with a full fledged list of capabilities for a cloud based Automated Form Generation and Analysis system as mentioned below:

• Form Analysis Information Collection:

  • Gathers industry profiles, government regulations, form field justifications, data policies, and benchmarking information.

  • Information can be input by users or obtained automatically through web crawling and natural language processing.

• Form Generation and Analysis:

  • Can generate new forms or analyze existing ones based on collected information.

  • Uses field tags, natural language processing, and optical character recognition to analyse form fields.

• Scoring System:

  • Generates various scores including form privacy score, form justification score, organisational privacy score, overall privacy score, combined form score, field combination score, and benchmarking score.

  • Scores are calculated using data structures, predictive models, machine learning, and artificial intelligence.

• Recommendations:

  • Provides recommendations for form improvements based on generated scores.

  • Suggestions may include adding/removing fields or using alternative forms.

• Automated Actions:

  • Can automatically generate forms, add/remove/replace fields, or update forms based on scores.

  • Implements security features like access credentials or encryption based on risk scores.

• Continuous Learning:

  • Uses AI and machine learning to analyse form inputs and update risk scores.

  • Scans the web for data breach news to adjust risk scores dynamically.

• Benchmarking and Comparative Analysis:

  • Generates benchmarking scores to compare an organization's forms and practices with industry standards, geographical norms, and peer organizations.

  • Allows comparison of form privacy scores, justification scores, and organisational privacy scores across similar organisations or within the same industry.

  • Provides visualisations to display how an organisation's scores compare to industry averages or peer organisations.

  • Enables organisations to understand their relative position in terms of data privacy and form security within their sector or geographical region.

We adopted the lean methodology of product development, the idea was to build an MVP to validate the problem-solution fit and then once we engage with a partner build a full fledged data privacy solution catered to their needs.

Minimum Viable Product:

In 3 months time, we were able to build a working demo for a data privacy risk assessment concept, that could work on multiple levels:

• Understand the industry data collection, storage and sharing needs.Identify the categories of data collected- demographic, financial, lifestyle, medical and others.

• Understand the organisation data collection, storage and sharing needs. Identify the field level details collected, whether sensitive PII details are stored in an encrypted format or a non-encrypted format. Does the organisation have a valid business case for the data that is captured by them but are not collected by other peers in the same industry.

• Peer group comparison with respect to data collection, storage and sharing needs. Comparing the responses from the organisation with the scores from others in the same industry, geographies and having similar business operating models.

The next stage was to gather feedback and refine the idea further.

Gathering Feedback for Automated Form Generation and Analysis:

For gathering feedback, we were looking for avenues where we can showcase the demo, explain the idea and the future roadmap to refine this further. In side PSCOE, we were operating like an early stage startup with a lean team therefore I had to wear multiple hats and think about how do we create buzz around this idea within and outside the organisations:

• Create pitch decks and teasers:

  • Market opportunity

  • Problem statement

  • Regulatory perspective

  • Communicating the big picture about the solution, future roadmaps

  • Showcase- demo

  • Testimonials

• Creating awareness:

  • Roadshows and installing kiosks/stalls/flyers within the organisations to create awareness among the internal stakeholders. This was to build organic word of mouth among internal stakeholders who can become our advocates while talking to the clients.

  • Managing client visits to showcase the demo and gather real time feedback from Accenture's leadership and client CXOs.

  • Publishing articles in the newsletters that was shared with various client stakeholders.

We received a lot of important and valuable feedback to refine the idea around solutions, positioning and also filing a patent to protect the original IP. We incorporated the feedback and also received a go ahead from Accenture leadership for filing a patent application.

We started our patent journey by talking to the patent attorneys hired by Accenture. We explained them all about the IP and post multiple clarification calls, our actual paperwork started. Patent application to grant is usually a long process. At this stage, we also included Accenture's internal pre-sales team to pitch the product to potential clients and generate interest.

Unfortunately after a couple of months, I decided to move to a new organisation. However I kept following the patent status through the USPTO portal. The patent was granted in 2021, almost five years after we started the application process.

Key Learnings from the entire experience:

The Public Service Center of Innovation and Excellence provided me with an extraordinary opportunity to think and work like an entrepreneur. It helped to gain experience in:

1. Identifying a problem, conducting market and user research.

2. Validating your ideas by building MVP and gathering feedback.

3. Creating product roadmaps and communicating the roadmap to the leadership to build conviction.

4. Showcasing the assets and big picture to CXOs from Public Service Organisations.

5. Creating artefacts, conducting roadshows, managing client visits gave a very good exposure to pitching the idea, get real time feedback, tackle questions on the product.