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Posted on: March 12-2018 | By : Rahul Ganar | In: Life Sciences | No Comments

Although high-profile data breaches grab the headlines, behind the scenes, life sciences is just as information sensitive as any industry. Any pharma company faces a major challenge when it comes to complying with the myriad regulatory requirements about how they create, handle and submit documentation about the products they manufacture.

Even a minor slip up can have a serious financial impact in the form of fines, penalties, or delayed product launches. With so much at stake, document management is a critical process for any pharma companies.

There are a number of widely-accepted best practices to ensure compliance with regulations, but many of these are extremely complex to implement, meaning that the industry has struggled for years to put them in place. These include:

  • Harmonizing and standardizing all global regulatory submission templates
  • Keeping on top of changing and emerging requirements and timelines
  • Implementing strong versioning and change management practices
  • Maintaining strong governance and process management controls
  • Capturing key performance metrics and feedback from regulatory authorities

At Syntel, our prescription to these challenges is a suite of end-to-end regulatory services, driven by an intelligent regulatory services platform. We combine the power of automation and decades of business process expertise to implement standardized, trusted processes for regulatory operations and submissions to health authorities. We can deliver business outcomes such as:

  • 20% reduction in regulatory writing and submission publishing time
  • Dramatic improvements in submission quality
  • Consistent templates for all clinical documents
  • Easier document lifecycle management

A huge added benefit to more structured and consistent document management is the ability to capture rich metrics at every step in the process. By making the document initiation, preparation and publication process more transparent, we can deliver deep insights into your operations and make continuous process improvement a reality.

If you are ready to take the next step in your document management operations, visit us online at

Rahul Ganar

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Rahul Ganar
Rahul Ganar, Senior Business Analyst, Life Sciences, Syntel has more than 10 years of domain and IT...

Posted on: December 01-2017 | By : Subhajit_D | In: Artificial Intelligence,Industries,Project Management | 2 Comments

The 2001 French romantic comedy Amelie told the story of a shy waitress who decides to change the lives of those around her for the better, while struggling with her own isolation.

The painting below captures one of the 222 moods that the main character depicted in the movie. It was drawn by an aspiring artist that claims the goal of the project was, “To be taken seriously — one day — as a creative artist in my own right.”

Before we continue, see if you can answer the following two questions:

  1. Who is the painter?

  2. Why are we talking about a movie and a painting when this article is supposed to be about merchandizing and AI?

To answer the first question, the name of the painter is The Painting Fool, an AI enabled computer program that skillfully simulates the painting process. However, the answer to the second question is much more interesting.

Merchandising and the role of merchandiser has always been about creating a relationship between a brand and a consumer, to the extent that it evokes a strong emotion and a behavior. Merchandisers are the fuel that drives a store’s vision for inventory, tells a compelling story that influences customer desires, helps them relate that feeling to a product line, and triggers the sale.

While there are more or less “scientific” merchandising principles, formulas and theories, the knowledge, experience and intuition of the retailer brings something indispensable to the table – the “art” of merchandising. This brings us squarely back to the answer to question #2 above.

At Syntel, we always keep an eye on the horizon, and have been steadily investing in developing an ecosystem where designers, merchandisers and buyers will leverage AI to predict what customers want before they even know themselves.

We believe that the future of Merchandising will capitalize on the inherent creativity of the human mind, backed by AI-driven creative algorithms. Clearly, merchandising design and planning requires a lot of creativity and prediction to succeed, and AI and ML will help lead the path forward.

As a trusted technology partner, Syntel can help our clients harness AI and ML to progress in their Merchandising journey by focusing on:

  • Customer Experience AI: Assemble and recombine a series of components and thousands of potential configurations to identify factors that drive maximum impact and saleshe painter?

  • Managing Variations through Automation: Define and manage automation algorithms and large data sets that use continual iterative A/B testing to pick “winners” for customer latent needs

  • Mental and Data Models to Recommendation Engines: Use a data-driven approach to build inputs that run the recommendation engines

  • Capturing Nuanced Customer Triggers and Signals: Capture and identify the customer responses of and discover insights that define discovery of next generation traits

If the pundits are right and AI truly does take off as predicted, this technology will have a role to play in virtually every aspect of our lives. If the work of The Painting Fool is any indication, even creative fields like Merchandising may experience a “bot” explosion. To capitalize on this wave of innovation, you need a partner that is well-versed in the latest technology but has a deeply-rooted understanding of your business.

To find out how Syntel can help, please reach out to your Syntel Client Partner or learn more about our AI and Machine Learning solutions online at


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A graduate from IIM Calcutta with 10 years’ experience in the industry, Subhajit Dutta is a...

Posted on: October 06-2017 | By : Prasanna Sukuru | In: Agile,Project Management | 1 Comment

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    We are all aware that in Scrum teams, a great deal of importance is put on team collaboration, positive team dynamics, face-to-face communication, responsiveness to change, early feedback to customers and ROI – all in a fast paced setting.


    That puts a great deal pressure on the teams, so it helps have an additional edge apart from the high technical competencies required. So, what kind of edge?


    For starters, I believe one way to get that edge is to embrace mindfulness, a spiritual concept which is defined as paying attention in a particular way: on purpose, in the present moment, and non-judgmentally.


    There would seem to be no apparent connection between the two concepts, since Scrum is a hard-boiled project management methodology, while mindfulness may have stronger associations with a Yoga studio than a Scrum room.


    However, mindfulness helps promote openness, reflection, discovery, flexibility, adaptability, focused evaluation, and pragmatic decision making. These in turn are closely linked to benefits like increased creativity, innovation, emotional intelligence, empathic interpersonal relationships and the flexibility to accept change — all of which are critical to success in Agile teams.


    Below, I have illustrated the close connection between Agile philosophy and the principles of mindfulness.


    Agile Philosophy Mindfulness Principles
    Individuals and interactions over processes and tools Empathy Awareness
    Working software over comprehensive documentation Focus Motivation
    Customer collaboration over contract negotiation Non-Judgement Empathy
    Responding to change over following a plan Awareness Empathy

    It would appear that there is some overlap between mindfulness and Agile, so let’s look at two such core principles that can contribute to higher productivity and greater success.




    Both Agile and mindfulness focus on the ability to listen, understand, and use skill to respond to the needs of others.


    By strengthening and leveraging emotional intelligence through mindfulness techniques, Agile teams can learn to listen better and establish better connections with both the customer and within the team itself, which in turn boosts quality and productivity.




    One of the twelve principles outlined in the Agile manifesto is simplicity. The focus is on high value yet simple processes and solutions that reduce waste and increase quality.


    Mindfulness helps people become aware of unnecessary mental clutter, and enhances the skill of making simple choices. Someone practising mindfulness can identify and let go of energy-draining thoughts like negativity and uncertainty before they become problematic.


    Similarly, Agile focuses on simple designs, short meetings, and avoiding long discussions. Activities are organized based on priority and efficiency, which requires teams to be extremely focused and driven. Mindfulness techniques like emotional de-cluttering can help teams focus better.


    How to Apply Mindfulness Techniques


    There is more than one way to practice mindfulness, but the goal of any mindfulness technique is to achieve a state of alert, focused relaxation. This is achieved by deliberately paying attention to your thoughts and sensations without judgment, and steering the mind into the present moment.


    There are many techniques that take very little effort and can be done practically anywhere, anytime, such as Meditation, Mindful Immersion, Mindful Observation, Mindful Appreciation, Mindful Breathing and others. Below are some pointers on two important techniques.




    Broadly speaking, all mindfulness techniques are a form of meditation. Meditation is about remaining calm and effortless in an uncertain world. The Agile/Scrum world is set-up to respond to unpredictability, whether it’s changing user requirements, deliverables, deadlines, or unforeseen glitches.


    Meditation does the same. You go with the flow of your feelings, whether pleasant or unpleasant, and never push or force your mind or thoughts.


    The benefits or meditation are well-recognized and quantifiable. In fact, one insurance company reported a decrease in healthcare costs and an increase in productivity among employees trained in mindfulness/meditation. Many Olympic athletes attribute their success to meditation practices, and Google even has a formal employee meditation program, whose motto is, “Greater complexity outside requires greater clarity inside.”

    Mindful Breathing


    Another important aspect is focus on the breath, which is closely linked to our emotions and sense of well-being. Breathing techniques, when practiced regularly, foster more positive emotions and help steer an anxious, angry or regretful mind back to the present moment.


    In the Agile world, being in the present moment is essential, especially during a Sprint. It won’t help if the team is bogged down by thoughts of past Sprints or future Sprints. In the moment, the Sprint must become like your own breath, and one of the best ways the team can get back on track is to make the sprint commitment the clear focus of attention for everyone.


    Still skeptical? The only way to prove me wrong is to try promoting mindfulness on your own team.

    There’s literally nothing to lose, yet you stand to gain a more positive environment, happier Scrum teams, increased productivity, greater flexibility and adaptability, better focus, and clear-headed, pragmatic decision making.


    Try it out and let me know how it works on your team. Or, comment below and share your own experience with mindfulness.

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    Prasanna Sukuru is a Principal Consultant and leads Syntel’s Agile Center of Excellence. She has...

    Posted on: October 04-2017 | By : Guninder Bhatia | In: Agile,Artificial Intelligence,Project Management | 4 Comments

    With the recent trend towards automation, machine learning and artificial intelligence (AI), it appears that the application of AI can not only transform enterprise computing, but now has the power to change project management as well.


    For a while now I have been exploring AI, and how developments in AI can benefit project management – be it traditional or Agile.


    A Quick Background on Bots and AI


    The most common definition of AI is intelligent behavior exhibited by machines, and a Bot is simply software that performs a task on the user’s behalf. (Wikipedia gives a good general definition of AI and Bots)


    AI is already being used in many areas like speech recognition systems, search engines, personal digital assistants like Siri, self-driving cars and many more. One of most prevalent examples of an AI application is a chatbot — a computer program that mimics conversations with people via audio or text, using simple command line-like interfaces or natural language processing.


    With the increased use of messaging apps like Slack, chatbots are becoming the interface of choice for executing repetitive tasks.


    The Role of Bots and AI in Agile Project Management


    As a Project Manager, I spend a great deal of time manually tracking projects and creating reports and charts to share the status of a project. This undertaking can deliver accurate and useful information, but often, highly talented (and highly paid people) end up burdened with tedious administrative tasks. Instead, they should be doing things more suited to their talents — like prioritizing the roadmap, working with a customer or managing a key stakeholder’s expectations.


    According to Gartner, they estimate that “by 2030, as much as 80% of routine work— which represents the bulk of human hours expended across today’s PPM disciplines — could be eliminated as a result of collaboration between humans and smart machines.”


    With respect to Project Management (especially Agile Project Management, where automation is an essential part of the continuous delivery journey), AI has a significant role to play.


    Bots and AI can be an excellent option to automate regular project management tasks, enabling skilled staff to focus on other high-value intellectual activities instead. It can not only automate simple tasks, but also uncover insights on project performance and perform more complex tasks and make recommendations — something that only Project Managers are capable of today.


    PM Bots Currently in the Market

    • Stratejos — Assists with estimates, budget, and sprint management
    • Memo — Assists with team knowledge management
    • Hugo — Manages team learning and knowledge management
    • HipChat — Quickly checks the status of a JIRA task (not an AI Bot)

    Agile Project Management bots can drive ALM tools to trigger events or user requests. Agile Bots can automate tasks based on predefined rules or via sophisticated algorithms, which may involve AI.


    Simple Bots can be used for a variety of tasks, including automated report generation, adding tasks to the to-do list, or sending out task reminders. However, adding AI into the mix can provide a level of service that rises above many of the bots available today. Some of these use cases could include:


    • Facilitating Daily Standups :At the end of the work day, an intelligent Bot can connect with team members and ask for the status of an assigned task. Each team member will respond with an update on what is completed, what is in progress, and any roadblocks.
    • Publishing Daily Status Reports :Before the daily scrum, the Bot can create a report with a breakdown of all tasks the team members are working on, or any major roadblocks they are facing.
    • Task Assignment :AI-powered Bots can automatically assign tasks to the most qualified team member for upcoming sprints, based on the team member’s expertise.
    • Sprint Planning: A Bot can generate an alert if a sprint has too many or too few tasks for the team. Likewise, it can identify team members that are overloaded or have too few tasks on their plate.
    • Bug Tracking and Assignment: Bots enabled with AI can track and identify updates made to source code, and link those changes to the team members who made them. This enables real, actionable tracking of team performance, and makes it easy to assign follow-up tasks to the right team member.
    • Risk Alerts : With the use of advanced analytics, Bots can proactively generate alerts if there is a risk of over budgeting and estimation, and drill down to understand where things are going wrong.
    • Recommending Best Practices :Bots can also show which best practices need to be followed and which ones are not creating any business value. It can also link the impact back to project metrics, to better understand the rationale for a particular practice.


    Where Do We Go From Here?


    Ultimately, an AI system or AI Bots will improve outcomes while saving time and manual effort. However, there are some challenges, as these early AI tools for Agile Project Management rely on capturing and maintaining data correctly, which itself requires human intervention.


    Thus the question: Can a machine or Bot eventually imitate the intellect of project managers and replace them?


    In my opinion, there is currently no threat of this. Perhaps in the future they may begin to approach our level of intellect and decision making, but for now they are simply useful tools we can employ to take our team performance and productivity to the next level.


    What are your thoughts? Will the Bots replace us eventually, or are they just a means to an end? Comment below!


    For a while now I have been exploring AI, and how developments in AI can benefit project management – be it traditional or Agile.

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    Guninder Bhatia
    Guninder Bhatia works as a Business Analyst, Healthcare Practice with Syntel. She has over five...

    Posted on: July 17-2017 | By : Gauri Deshmukh | In: Industries | No Comments

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      Pharmaceutical companies are often among the largest and most complicated organizations in the private sector, which are constantly under close scrutiny and subject to complex regulation. Their business success depends on the timely and successful completion of clinical trials. Clinical trials generate incredibly complex data and unless there are efficient processes and modern technology in place, numerous problems can occur. Without the right processes and supporting technology, pharmaceutical companies can pursue a flawed trial or flawed compound for too long and fail to cut their losses. Even if the trial design is good and the compound is promising, the inability to collect, manage, analyze, and package the clinical data can produce long delays that cause costs to soar and keep the drug from hitting the market.

      A deeper look at each step of the drug development process reveals a recurring theme of missing, incomplete, or erroneous data that wastes time and resources and adds months or even years to the drug introduction process.

      It is imperative for pharma companies to master the key entities in clinical trial data for real time feedback on trial progress and patient compliance, reducing the overall elapsed time and cost of clinical trials.

      Current data issues in the pharma industry

      • Lack of consistency in creating unique identifiers for products, projects, studies, sites, investigators, and other key data across the company hampers project management and cross-functional communication and coordination

      • Insufficient enforcement of clinical study data standards significantly increases processing cost at multiple stages and compromises study quality – potentially placing patient safety and entire development projects at risk

      • Difficulty in locating documents in a timely manner, due to inaccurate or incomplete document metadata tags, poses (potentially critical) risks to regulatory submissions and inspections

      When is data considered to be of high quality?

      When the data:

      • Is accurate, current, consistent, complete, and relevant
      • Possesses integrity (e.g., unique identifiers, no duplicates, and parent-child records are properly linked)
      • Can be easily accessed across systems
      • Can be easily processed and analyzed for multiple uses
      • Retains all of the above, even as data volumes grow and new data sources and integrations are introduced

      How can this be achieved?

      A robust Master Data Management (MDM) Solution can help achieve all of the above by offering a customized solution in the near term, mid term, and long term, aligning to the strategic needs of the customer.

      Master data management has helped customers achieve great successes in other industries. It’s now time for the pharma industry to use this solution to achieve the below benefits:

      • Simplified business operations, standardized processes and better cross functional collaboration for study, site, product, project, investigator, and subject enterprise assets management
      • Single source of truth to publish these key entities to all the required stakeholders/systems across the enterprise
      • Facilitate connecting the dots to identify new business opportunities and facilitate strategic decision making by providing consistent, consolidated, standardized, enriched, accurate, and inter-related master data to reporting and analytical systems


      The global digital disruption affects the pharmaceutical industry as much as any other industry. The companies that succeed will be the ones that best manage, use, and share data.

      Transformation, however, is not necessarily an immediate change. Especially in large companies, new processes and technologies will be implemented over time and potentially a large number of individual projects. Each project will need its own justification, delivering a measurable return on investment. Using MDM to deliver the master data needed for each project’s success accelerates RoI on each project by making it easy to rapidly find and reuse the data required for an individual project.

      MDM helps us by providing processes for how we collect, summarize, and cleanse our data to ensure consistency, and appropriate governance in the ongoing maintenance and use of this data.

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      Gauri is a domain Consultant for Clinical Data Management. She has more than 11 years of Domain...


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