Going Paperless 2.0

On Lee, CEO & CTO GDP Labs and CTO GDP Venture

FULL DISCLOSURE: GDP Venture has invested in CATAPA, Djelas.id, Konvergen.ai, Datasaur.ai, GLAIR.ai, and Prosa.ai.

Paper Cost and Issues

Do you know the cost of running a paper-based business?

Paper has been around for over a thousand years. Johannes Gutenberg started the printing revolution in the 15th century. He won first place among the 100 most influential people of the last 1,000 years in Biography of the Millennium, ahead of Isaac Newton, Martin Luther, Charles Darwin, William Shakespeare, and Albert Einstein.

The U.S. Environmental Protection Agency reported the world produces 300 million tons of paper every year. Lindsay McGuire revealed the paper usage in offices and the true cost of paper:

• 70% of the total waste in offices is made up of paper.
• 30% of print jobs are never even picked up from the printer.?
• 45% of paper printed in offices ends up trashed by the end of the day.?
• USD 20 to file a paper document, USD 120 to find misfiled documents, and USD 220 to recreate a lost document.?
• Pulp and paper is the third-largest air, water, and land polluter among all industries in Canada and the U.S.?
• Paper production is the third most energy-intensive of all manufacturing industries.?
• Paper processes are known to be costly, inefficient, and unsecure.?

The Record Nations study showed that more than 70% of businesses would fail within 3 weeks if they suffered a catastrophic loss of paper-based records due to fire or flood. Additionally, office paper consumption will double in less than four years.

There is a cheaper, faster, easier and safer alternative to paper leveraging exponential modern technologies like Artificial Intelligence (AI), cloud, mobile, web, big data and security technologies.

Going Paperless 1.0

Many pundits predicted that the world would go paperless as PCs became mainstream in the 1990s and the Internet has made it easy to share documents. Phil Ydens, Adobe’s VP Engineering for Document Cloud, estimated there may be up to 2.5 trillion Adobe PDF documents in the world since it was invented in 1993. Additionally, there could be additional a few trillions of Microsoft Word documents since it was released in 1983.

Despite trillion copies of digital documents created for the past few decades, there is actually more paper being printed as printers become affordable, available and easy to use. It is counter-intuitive. Worldwide consumption of paper has risen by 400% in the last 40 years.?

How do you file and retrieve those digital documents scattered across various public clouds, company servers, employees desktops, laptops, tablets and smartphones? How many of them are outdated, inaccessible and lost?

Going paperless 1.0 had limited success because although it has solved some problems, it introduced new problems.

Going Paperless 2.0

Over 5 billion people use the Internet daily and there are almost 2 billion websites. 306 billion emails are sent and 500 million tweets are made everyday. Information overload! People are using search engines like Baidu, Bing, Google, Naver and Yandex to find relevant information quickly.

Why can’t companies do the same thing for their internal documents? It is technically doable because any company’s documents are only a small fraction of the documents available on the Internet.?

Companies should do what search engine companies do. They should index all the documents so they’re easily searchable by the users.? This will help the employees to find the information quickly.

How to Implement Paperless 2.0?

Going Paperless 2.0 might become closer to reality with the advances in exponential modern technologies like AI, cloud, mobile, web, big data and security technologies.

Going Paperless 2.0 is one of the prerequisites for digital transformation.

The following are step-by-step how to implement paperless 2.0:

• Step 1: Digitize hardcopy documents – Companies have accumulated hardcopy documents for years. They need to digitize the existing hardcopy documents into text. Optical character recognition (OCR) is the electronic conversion of images of typed, handwritten or printed text into machine-encoded text. It could do the conversion automatically with a high degree of accuracy. Konvergen.ai, a Datasaur company, provides OCR technology to convert some Indonesian documents to texts. For example, KTP, Kartu Identitas Anak (KIA), NPWP, BPKB, Kartu Keluarga, STNK, Passport, Kuitansi, Tagihan, Faktur,?Debit/Credit Note, Invoice, Sertifikat Tanah, Packing List, Container List, Beneficiary Certificate, Insurance, Certificate of Quality, Certificate of Wood, Certificate of Origin, Bill of Lading, Letter of Credit?, Parking receipt, Toll receipt, Gasoline receipt, Groceries receipt, etc. Konvergen could easily support other documents by training their OCR technology.
• Step 2: Replace paper-based process – Replace paper-based process with digital process. Change the company policy workflow from paper to digital. The formal wet signature could be replaced by digital signature services providers which have been approved by the government. For example, TékenAja! by djelas.id provides digital signature, e-meterai and e-stamp services.
• Step 3: Digitize PDF documents – Digitize all image-only PDF documents into text. Konvergen.ai OCR technology could handle PDF, too.
• Step 4: Digitize recorded audio -- Convert recorded audio reports, phone conversation, meetings, etc into text. Prosa.ai speech-to-text technology could do the job.

• Step 5: Store the documents on a centralized server – Put all the documents on a centralized server.
• Step 6: Index the documents – Index all of the documents.
• Step 7: Label the documents – Label some of the key documents to convert dumb data into smart data. Datasaur provides the labeling tool.
• Step 8: Apply NLP technology – Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language. It could autocorrect, find relevant documents quickly and convert smart data into useful information. Prosa.ai provides the NLP technology for Bahasa Indonesia.
• Step 9: Deploy a search engine – Give users access to these documents by using a search engine. It could autocomplete and find relevant documents your search quickly in under a second.

• Step 10 - Analyze the digital documents – Companies could unlock the hidden goldmine by analyzing the digital documents so they could make data-driven decisions. Most importantly, you could do it hourly, daily, weekly and monthly. GLAIR.ai could integrate Datasaur OCR and Prosa NLP technology to provide end-to-end solutions.

The users could retrieve all the company digital documents easily and quickly from anywhere at any time just like the way you search information on the Internet using search engines. It solves the paper based and Paperless 1.0 issues.?

In other words, you have a Google-like search engine for your company's digital documents.

Case Study: Consensus and Datasaur

Science-based answer app, Consensus and NLP data-labeling platform,?Datasaur have officially announced their partnership. Within a few months of integration, it was clear Datasaur’s NLP labeling technology would be a huge benefit to the Consensus Machine Learning (ML) model, enabling highly accurate results.

Consensus is building a search engine for scientific research which uses machine learning and natural language processing to make authoritative science-based answers accessible to everyone.

In order for Consensus’ state-of-the-art machine learning system to effectively analyze and extract information from scientific literature, they needed to construct quality datasets to train models. Datasaur was ready to help with an annotation product that:

• Labels scientific papers at different levels (entity, sentence, multiple sentences, etc.)
• Allows the creation of custom label sets
• Enables multiple annotators in the same file
• Supports inexperienced annotators (in this case, Ph.D.’s and Ph.D. students)
• Provides easy to use workflow tools
• Datasaur's platform was able to accommodate all of Consensus' complex annotation requirements and more.

Case Study: Adoption of OCR Technology by Major Industries

Virtually all major industries -- banking, financial services, insurance, healthcare, retail, tourism, logistics, transportation, government, manufacturing, government agencies, education, etc – are adopting OCR technology combined with AI, cloud, mobile, web, big data and security technologies as part of their digital transformation.

University of Georgia School of Law Library explained how they use OCR to update older PDFs in their institutional repository. It improves their website Search Engine Optimization (SEO) and their customers’ experience in searching and downloading millions of documents.

CATAPA, an intelligent payroll platform in Indonesia, uses Konvergen.ai OCR technology to convert various type receipts automatically using a mobile phone. The manager and HR will be notified so they could approve and reject the reimbursement claims digitally. This mobile-based digital process is not only more efficient but safer and healthier during the pandemic where most of us have been working from home for about two years.

BCA Group provides banking, financial services and insurance (BFSI)?is one of the largest public companies in Indonesia. They have adopted many modern advanced technologies like AI, Blockchain, Cloud, Data, Mobile, Web, Security, etc. They are using Konvergen.ai OCR technology to process various documents in Indonesia. For example, E-KTP, NPWP, Invoice, Letter of Credit, surat instruksi, NPWP, BPKB, STNK, Kartu Keluarga (KK), and License plate.

Once those documents are converted to text, they could become a goldmine. For example, BPKB contains detailed car info like plate number, brand, type, year made, machine number, made in which country, import information, dealer name, owner, etc. AI-powered big data analytics could give invaluable insights about the customers, cars, car trends, values, etc. to increase revenues, manage and reduce risks.

The Grand View Research that the global optical character recognition (OCR) market size was about? USD 8.93 billion in 2021. It will reach USD 33.44 billion in 2030.?

Conclusion

Company could empower their employees to become knowledgeable workers by converting dumb data to smart data and giving them access the information on their finger tips from any device anywhere anytime. They could make data-driven and informed decisions in a timely manner.?

Consequently, it improves internal processes, increases productivity, reduces costs and increases revenues.?

Additionally, it improves your stakeholders' -- customers, partners, executives, investors, etc -- experience since they could search your documents easily via your websites.

Furthermore, save the trees and environment for our children by Going Paperless 2.0 to comply with the world-wide effort in Environmental, Social, and Governance (ESG) initiative!