Transforming Life Sciences Through Knowledge Work Automation

The transformation power of technology is intertwined with efficiency and progress. Despite emerging challenges, automation offers practical efficiencies and benefits the life sciences sector are starting to consider in future growth planning and mapping workflow requirements

Knowledge work automation is at the heart of this digital transformation. It redefines how tasks are executed across various sectors. Work automation is essential for modern businesses, from streamlining routine processes to driving higher productivity.

The life sciences sector stands to benefit most from process automation. Life sciences encompasses biotechnology, pharmaceuticals, and healthcare. The sector has been significantly transformed by workflow and lab automation. More than 70% of life sciences organizations use automation for research and development processes.

This statistic illustrates how much life sciences organizations have embraced advanced data analytics and automation software development. For example, they are allocating significant resources to support each step of drug development.

The intersection of automation and life sciences is more than merely a technological meeting watermark. It represents a pivotal moment in pursuing innovations that can reshape the industry. This includes both drug discovery and medical research.

The Evolution of Knowledge Work Automation

The concept of automating business tasks has evolved. Changes started with the automation of labor during the Industrial Revolution. It continued with the advent of early computing systems.

Knowledge work automation has come a long way thanks to emerging technology. Breakthroughs in artificial intelligence (AI), machine learning, and computing power have propelled automation beyond routine tasks and manual work.

Advanced technologies have empowered systems to manage high-level decision-making, data analysis, and complex problem-solving. Large to small businesses use workflow automation, from manufacturing to financial services and healthcare, to work smarter. It’s not just about reducing mistakes. It’s about gaining a competitive edge.

Applications of Work Automation in Life Sciences

Applications that improve the efficiency of scientific processes in the real world include

  • High-throughput screening involves automated techniques that rapidly analyze large samples, allowing researchers to efficiently identify potential drug candidates and conduct robust experiments.
  • Data analysis and interpretation: AI automation can process vast datasets quickly and precisely. This helps scientists uncover meaningful insights and patterns.
  • Robotic process automation (RPA):RPA is increasingly crucial in life sciences R&D. Laboratory process automation leverages robotics to process and manage samples. It also streamlines repetitive tasks, increasing productivity and enhancing flexibility and agility. Benefits include reduced manual processes, heightened accuracy, standardized workflows, and cost savings.
  • Robotics in sample handling reduces the risk of human error and increases the throughput and accuracy of laboratory workflows.
  • Automated liquid handling systems perform precise and repetitive liquid transfers. This ensures accuracy in experiments requiring careful measurement and mixing. By automating these tasks, labs can achieve higher levels of consistency.

Benefits of Knowledge Work Automation

Information automation increases efficiency and will improve productivity. How? By relieving professionals of routine and time-consuming tasks. This allows researchers to spend more time on high-value activities. The quest to increase the speed of innovation and discovery is facilitated by knowledge work automation. It contributes not only to streamlined processes, but also to knowledge workers’ professional growth and effectiveness.

Knowledge work automation also drives enhanced data accuracy. Automated systems minimize the risk of human error, ensuring precision in analyzing data and interpretation. This improves the reliability of results and elevates the overall quality of R&D.

Advancements in information technology for life sciences include handling clinical trial data and improved document management for contract research organizations. These include streamlined workflows, enhanced collaboration, and reduced risks. This drives excellence in business operations and strengthens relationships with sponsors.

Integrating technology-driven solutions ensures advantages extend beyond efficiency gains. They positively impact the life sciences industry, from project management to regulatory compliance and enhance overall customer experiences.

Addressing Challenges with AI and Automation

What are some obstacles with the automation in life sciences laboratories?

  • Financial challenges hinder the adoption of process automation systems.
  • Long-standing obstacles in practices of academic research create resistance to future automation.
  • Despite expected progress in future design of affordable, lower-level automation equipment, the market still needs further development.
  • Meeting growing demand for environmentally conscious automation poses a challenge for developers.
  • Ensuring systems remain compatible with the innovative nature of researchers, preserving the freedom to create new protocols.
  • Life sciences researchers now need working knowledge in both traditional biology “wet lab” skills and emerging “dry” automation skills.
  • Spatial constraints within laboratories and cultural challenges contribute to knowledge gaps, leading to a lag in automation software

As automation continues to evolve, a higher elevation of tools and systems will emerge. They will be used to further enhance R&D efficiency and productivity. AI-powered drug design represents a significant trend in the future of work automation.

The long term shift towards AI promises to transform the identification of potential candidates. It will accelerate research timelines and enhance the precision of therapeutic interventions.

Another emerging trend is the seamless addition of decision automation in personalized medicine. Automation technologies are expected to be crucial in customizing medical treatments to individual patient traits. This trend encompasses the automation of processes related to patient data evaluation, treatment customization, and the efficient delivery of personalized healthcare solutions. The combination of automation and personalized medicine will optimize patient outcomes.



How does knowledge work automation in life sciences differ from traditional office automation systems?

Unlike traditional office automation, knowledge work automation in life sciences is customized for complex tasks in biotechnology, pharmaceuticals, and healthcare. It involves advanced processes such as data analysis, decision-making, and problem-solving.

Why should life sciences embrace the automation of knowledge work?

Automating knowledge work management in life sciences streamlines processes and save time. This allows professionals to focus on high-value activities and contributes to maximized effectiveness. It also accelerates drug development, healthcare, and medical research innovations.

What makes the automation of knowledge work disruptive for life sciences?

The automation of knowledge work in life sciences disrupts traditional workflows by introducing advanced technologies such as AI. AI improves speed, accuracy, and overall effectiveness. This disruption transforms how tasks are executed, fostering breakthroughs in healthcare, drug discovery, and research.


Automate Insurance Underwriting – The Need of the Hour

Insurance underwriting software


Is your insurance underwriting process slowing you down? Are you struggling to manage high volumes of paperwork? Are you taking more time to initiate new quotes and policies? Is a hard-coded legacy system inefficient to meet your requirements? Are you finding difficulty in determining risks?  Wondering how to overcome these hurdles? Simple, automation is what you need.

Why Automate your Insurance Underwriting System

An automated underwriting system helps you streamline the end-to-end process and enables you to make informed business decisions. The insurance underwriting solution comes equipped with robust functionalities, thereby enabling you to witness a host of business benefits, including:

  • Reduced errors
  • Minimized turnaround times
  • Higher operational efficiency
  • Improved compliance

Transform into a Truly Digital Insurer

Listed here are the seven simple ways to automate your policy issuance and underwriting system that will transform you into a truly digital insurer.

1. Managing a High Volume of Content

A content management platform helps underwriters manage a high volume of content, which otherwise is a cumbersome task. The system captures, digitizes, and extracts data from content generated across multiple channels

2. Analyzing Applications

An intelligent business process management platform helps automate the insurance underwriting process. It analyzes incoming applications, identifies the concerned areas, and sends straight-through processing if it meets all the given criteria. If not, it is sent for review

3. Generating Summary Sheet

An end-to-end insurance underwriting software helps consolidate the information collected from multiple sources and generates a summary sheet. The system helps gain a 360-degree case view to the underwriter

4. Enabling Error-free Underwriting

Optical character recognition (OCR) enables error-free insurance underwriting of quotes. Further, it ensures simplified policy issuance and underwriting

5. Initiating Case On-the-move

Mobile-based initiation platform helps field agents to initiate cases ‘on the move’, thereby reducing processing cycle times and improving customer experience

6. Analyzing Geo-specific Data

Satellite imagery data analyzes geo-specific data of a particular region. It determines the risk and helps caseworkers to decide the premium in a hassle-free manner

7. Finding Co-relations Between Claims and Risk Elements

Insurance underwriting solution is equipped with natural language processing that extracts texts and audio data, categorizes them, finds co-relations between specific claims and risk elements, and accordingly determines the premium

Insurance Underwriting Software

The Way Forward

Underwriting is one of the key functions in the financial world and plays an imperative role in gaining performance excellence. Hence, to make a reasonable profit in insurance, underwriters are required to intelligently assess risk and cover the losses of the insured and related expenses. Therefore, the need of the hour is to automate processes with end-to-end insurance underwriting software.


Giving Clients Access to Automation: It’s a good thing

When it comes to no-code document automation, the question invariably arises: How much access should be given to clients when it comes to template questionnaires, especially as it applies to legal clients? This could include external clients for law firms, those who are paying the law firm for legal services, or internal clients for in-house, those who are requesting services from the legal department.
You may be wondering why they need access to the template questionnaire at all! Let’s examine two scenarios: law firm-focused and in-house focused.

Law firms

The starting point for this use case is that the law firm’s employment team has a client who regularly onboards new people into their business, but only ever instructs the law firm to draft the most complex employment or consultancy agreements.

The day-to-day, less complex agreements are dealt with in-house and deemed not to be worth instructing the firm to complete because it’d be too expensive. However, the in-house team prepares their agreements manually (i.e., without automation).

There is a commercial opportunity here for the law firm to gain a stickier relationship with the client. The law firm knows they aren’t going to be instructed for this less complex work. However, it would be possible for the firm to provide the client an automated version of their less complex agreements. They would then be able to create those less complex agreements quicker and easier internally and the firm can provide this as a subscription service to the client.

This is one of the unique advantages of M-Files Ment over other document automation tools out there. In this scenario, it allows the law firm to automate an employment agreement and provide access to their clients. The law firm even has the ability to time limit it or cut off access if the subscription ends. If a more generic template is used it can also be scaled easily across multiple clients too.

Benefits for the law firm

• Additional regular revenue stream
• Stickier relationship with client
• Ability to provide better service to client
• Ease of use if using a more generic template to cover all subscribers

Benefits for law firm’s client

• Internal drafting can be completed more quickly
• Satisfaction law firm because they understand their needs and can help them
• In-house legal team has more capacity

In-house use case

For the in-house use case, the starting point is when a legal department is inundated with requests for NDAs or DPAs from internal clients, such as sales or procurement. Legal doesn’t want to provide these internal clients with the templates of the agreement because they don’t fully trust them to contract with external parties. Providing the template would give them too much flexibility to draft, possibly adding unnecessary obligations to the company or omitting clauses to “get things through.”

The ideal scenario is for the internal client to be able to draft the agreements with legal constraints built in—for example, restrictions on confidentiality period. The internal client is then able to create an agreement through a questionnaire which always incorporates these constraints—the result is a draft agreement that always contains approved wording.

M-Files Ment can provide such functionality in three ways, depending on the level of control required:

More control for internal client

With M-Files Ment, it’s possible for legal departments to provide the internal user with a link to the template questionnaire. The internal client can then get to the link, possibly through the company’s intranet, and fill the questionnaire. Upon submitting the questionnaire, they have access to the generated document and can then send it to the counterparty.

Less control for internal client

It’s also possible to provide the link to the business user, but when the internal client generates the agreement, it can either return back to a lawyer for review or only produce a PDF at the end to avoid freehand drafting post-generation.

No control for internal client

M-Files Ment also offers off-the-shelf the oneNDA and oneDPA automated templates—agreements designed to be easily and quickly agreed upon as they use market standard wording that shouldn’t be amended. If the internal client is generating these agreements, there will be very little scope to negotiate or make any changes.

• Control of requests for less complex legal documents
• Empower business users who can create their own drafts
• Less involvement of in-house legal team for first draft. They can be there to review only, saving time and freeing up capacity.

Benefits for internal client

• Empowered to create first draft simple legal documents
• No reliance on legal departments for first drafting, improving contract velocity
• Use of standardized wording templates allowing quicker agreement of contracts


The Importance of Knowledge Management in the Information Age

Modern organizations are awash with information, and utilizing an organization’s intellectual capital and accumulated experiences into something actionable for business has become a challenge in the Information Age. It’s a recognized competitive advantage to turn disorganized data repositories into efficient, easy to access, and searchable vaults of information. Because organizations struggle with effective and efficient ways to accumulate and leverage their intellectual capital, knowledge workers have lost opportunities to make timely and informed business decisions that would’ve benefitted from the client and market insights that Knowledge Management provides.

What is Knowledge Management?

As a concept, Knowledge Management is about equipping individual employees with the collective knowledge of the company so that people can harness prior work across the organization for the benefit of work in the present as well as the future. It in essence institutionalizes in-house knowledge for the sake of allowing your workforce to learn from and utilize core assets you have already created.
As time goes by, a great deal of the knowledge an organization creates is based upon collaboration, whether it’s derived from shared ideas between colleagues or insights picked up from interactions with clients or vendors. Capturing these lessons learned during everyday exchanges is key to capturing knowledge into something that can be codified into processes and checklists and utilized for the benefit of the rest of the company long term.

Organizations looking to institutionalize knowledge capture can turn to information management platforms that that make collected information easy to re-use down the road and can offer helpful search tools and templates to locate, tag, and organize every in-house asset so that it can be called upon constructively and efficiently whenever it is needed.

Why does Knowledge Management matter?

We live in the Information Age where information itself acts like a powerful currency that an organization can leverage as intellectual capital in the marketplace. Organizations that can effectively capture, manage, and leverage their intellectual capital, will win more business, deliver client value more efficiently and outperform their competition.

In real world terms that means that organizations that do Knowledge Management well, are less vulnerable to losing subject matter expertise over the passage of time due to lost assets or staff turnover. And employees are liberated from the drudgery of inefficient information searches that research has shown eats up as much as 30% of a knowledge worker’s time. The bottom line here is that when employees spend less time searching for the insights they need, they’ll have more time to produce value-adding initiatives and be attentive to their actual job descriptions.

An all-too-common struggle for organizations has been keeping track of relevant existing assets that can win new deals or assist with projects currently in the pipeline. Whereas organizations that adopt Knowledge Management can properly tag documents with metadata and have benefitted from placing information in a context that facilitates its re-use in a relevant way later.

Additionally, by compiling knowledge into an accumulated knowledge bank, organizations can codify the lessons they learn over the years into checklists and processes that help ensure past mistakes are not repeated. The 2020 Deloitte Global Human Capital Trends revealed that 75% of respondents prioritized “creating and preserving knowledge” as an important strategy for their future and immediate business, and yet only 9% of those same respondents claimed they are equipped with the means to pull it off.

Possessing a platform that enforces, guides, and automates the steps required for knowledge capture and re-use ensures organizations are able to use Knowledge Management the right way. And in a way that can address concerns about redacting confidential client information from people not authorized to see certain things by implementing automated workflows that help ensure a flawless anonymization process with reviews, approvals and publishing. Knowledge Management can also streamline organizations with periodic reviews of assets to help maintain the most current versions, archive anything that is obsolete, or apply new tags as internal terminology evolves.

All of this points to the reality that as the business landscape continues to evolve, leveraging knowledge from within an organization is now a priority and no longer simply a “nice-to-have” luxury. Those that aren’t thinking about adopting Knowledge Management are already behind.

How can M-Files help make a difference?

The end goal of Knowledge Management is really to future-proof your organization by codifying your institutional knowledge and avoiding any repeat of past mistakes. Because at its most basic level, Knowledge Management is all about allowing knowledge to be filed and re-used as an asset. Properly done, Knowledge Management means avoiding ever having to re-invent the wheel by enabling all employees to call upon accumulated assets and to improve workflows and become more proficient in what they do, regardless of their level of expertise.
And when M-Files enters the equation as the single source of truth for all enterprise data, the task of Knowledge Management becomes that much easier. M-Files is a metadata-driven information management platform that was designed to address common knowledge management challenges with tools that automate processes related to capturing, codifying, and re-using knowledge that can be leveraged for business time and time again.

The metadata-driven M-Files platform can address common Knowledge Management challenges to help capture, codify, and re-use knowledge. With metadata, views, enterprise search, templates, and workflows, M-Files provides the right tools for organizations to keep up with the new realities of doing business in the Information Age.