Les Misérables and the Digital Workplace

When Optimizing Data Access Shows Soft and Hard ROI

When Optimizing Data Access Shows Soft and Hard ROIs

Les Misérables? Ring a bell?

Of course! This is a famous book by Victor Hugo, and the story is amazing! But what does it have to do with the digital workplace? Let me focus on a specific quotation and comment on similarities with the digital workplace.  It occurs in the chapter where Jean Valjean and Cosette are residing in a house with a garden.  In that part, Victor Hugo explores the multiple dimensions of nature.  What caught my attention is the following question: “Where the telescope ends, the microscope begins.  Which of the two has a grander view?”  The quotation resonated in my mind as it evokes similarities with the digital workplace, particularly in reference to data access.  For large and diverse content, having relevant and timely information is critical to companies.  There are different methods to query the data and the kind of ROI that can be expected varies by orders of magnitude.

The telescope – see far into the universe

What does it mean for the digital workplace? This means breaking internal data silos and opening up global information to your entire organization (any information shared by all, such as policies, procedures, HR information, compliance, etc.).  Having a digital workplace that includes an enterprise search layer that connects people to corporate content is therefore critical.  Every employee can see beyond its reach and access data spread over a wide range of different repositories.  This data is made available to everyone and everyone stays informed.

Such use of enterprise search does not bring a high degree of business specificity.  This is typically a Google-like experience with a simplified interface that is used indifferently by marketing, sales, engineering, or accounting people – any employee.  Working across business units to address multiple audiences (a horizontal approach) – its value can be uncovered by helping a large number of employees to find information; the ROI (Return on Investment) is based on an overall improvement of the company’s productivity.  According to McKinsey, employees spend close to two hours per day search for information.  In addition to increased productivity, such employee empowerment also has positive impacts on a company’s culture and employees’ wellbeing.  This is what we call a soft ROI.  A soft ROI is not easy to measure and rely on in a business case.  Benefits are referred to as indirect.  Having said that, some dollars savings can be estimated through productivity gains.  The main assumptions include the number of employees,  the average salary, and the percentage of working time saved thanks to a simple information finder.  A summary of an ROI that was calculated for a company comprising of 30,000 employees can be seen below.

ROI of Search for Digital Workplace

Assumptions were made regarding user adoption ramp-up schedules, with a greater number of users and a higher efficiency over time.  The ROI in this example is close to 13 million dollars over 3 years.

The microscope – explore what is next to you

How would this translate for the digital workplace? This ability would indeed be very helpful to assist intensive-knowledge workers in their daily tasks.  The term “knowledge worker” was first coined by Peter Drucker who defined knowledge workers as high-level workers who use advanced data collection techniques, statistics, complex correlations, case studies, and a lot more.  Data is key in helping them to perform their jobs.  And guess what? Enterprise search technology can also help in such a context.

As opposed to the simple Google-like experience, the objective here is to design a “Search-based application” customized with business-specific knowledge.  The value resides in the ability to follow a targeted business function along the key phases of its work.  Only enterprise search can index and aggregate very diverse data coming from both structured and unstructured content in order to extract the nuggets of information and provide a unified view on a specific topic (product, customer, company…)  For example, for a bank advisor, it is critical to aggregate internal data such as payments, information from the CRM, transaction history as well as external data, such as market analysis and news, to recommend the most relevant products to a customer.  The ROI is no longer related to a high number of people but to clear business-process improvements.  To do so, we target a precise group of knowledge workers on a designated use case in a specific vertical, a tryptic of “industry, use case, persona.”

Let’s take the example of clinical trials with a large pharmaceutical company.  Clinical trials are research studies that are aimed at evaluating a new drug.  They are the vehicles for evaluating a new drug.  They are the primary way that researchers find out if a new treatment is safe and effective.  In that case, the tryptic mentioned previously would then be “pharmaceutical, clinical trials, researchers.”  A specific “Search-based application” has been designed to dive into clinical data dispersed across millions of files and multiple systems and applications, surfacing insights to support the evaluation of new drugs.  The enterprise search technology had increased speed to market for new drugs.  Knowing that in the pharma industry, the average cost of new drug development is $1.0 billion, any slight improvement in the global process immediately gives better margins leading to bottom-line improvement.  This is what we call a hard ROI.  This type of ROI refers to clear measures that can be quantified in hard dollars.  To give you a flavor of the way the above pharmaceutical company calculated the ROI, you’ll find below some of the assumptions that were made (for your information, clinical trials include 3 main phases):

  • 10% to 14% of all drugs that make it to phase 1 succeed
  • 31% of all drugs that make it to phase 2 succeed
  • 50% of all drugs that make it to phase 3 succeed
  • 32% of drugs make it to phase 3
  • Average trial costs- phase 1: $170m; phase 2: $400m; phase 3: $530m
  • The cost of a trial is between $800m and $1.8b
  • The cost of patient/site recruitment averages $40k per patient/site

Locating key data and deriving insights is a key success factor for researchers.  The “Search-based application” has increased efficiency, shaving months off drug development timeline.  According to this large pharmaceutical corporation, the ROI realized is 25 million dollars per drug.

So, which has the grander view- the telescope or the microscope?

Both reveal worlds that are normally hidden from view.  For the digital workplace and data access, you require them both.  Accessing the right information at the right time is becoming ever more complex, and there are many factors with the potential to make it even more complicated.  Either for corporate content or business-specific data, enterprise search can help with both dimensions.  The ability to retrieve a company’s data assets and provide actionable insights in order to make informed decisions is indeed vital for business efficiency.  By applying methods and technologies, you can be sure that “Even the darkest of night will end and the sun will rise.” Another quote from Les Misérables.

Digital Workplace telescope vs microscope

+1Share on LinkedInShare on Twitter

How Biopharmaceutical Companies Can Fish Relevant Information From A Sea Of Data

This article originally appeared in Bio-IT World

Content and data in the biopharmaceutical industry are complex and growing at an exponential rate. Terabytes from research and development, testing, lab reports, and patients reside in sources such as databases, emails, scientific publications, and medical records. Information that could be crucial to research can be found in emails, videos, recorded patient interviews, and social media.

school-of-fish

Extracting usable information from what’s available represents a tremendous opportunity, but the sheer volume presents a challenge as well. Add to that challenge the size of biopharmaceutical companies, with tens of thousands of R&D experts often distributed around the world, and the plethora of regulations that the industry must adhere to—and it’s difficult to see how anyone could bring all of that content and data together to make sense of it.

Information instrumental to developing the next blockbuster drug might be hidden anywhere, buried in a multitude of silos throughout the organization.

Companies that leverage automation to sift through all their content and data, in all its complexity and volume, to find relevant information have an edge in researching and developing new drugs and conducting clinical trials.

This is simply not a task that can be tackled by humans alone—there is just too much to go through. And common keyword searches are not enough, as they won’t tell you that a paper is relevant if the search terms don’t appear in it, or if a video has the answer unless the keywords are in the metadata of the video.

Today, companies can get help from insight engines, which leverage a combination of sophisticated indexing, artificial intelligence, and natural language processing for linguistic and semantic analyses to identify what a text is about, look for synonyms and extract related concepts. Gartner notes that insight engines, “enable richer indexes, more complex queries, elaborated relevancy methods, and multiple touchpoints for the delivery of data (for machines) and information (for people).” A proper insight engine does this at speed, across languages, and in all kinds of media.

For biopharmaceuticals, this is particularly powerful, allowing them to correlate and share research in all forms over widely distributed research teams. Here are several ways biopharma companies can use insight engines to accelerate their research.

Find A Network Of Experts

Many companies struggle to create the best teams for new projects because expertise is hidden in large, geographically-distributed organizations with multiple divisions. A drug repositioning project might require a range of experts on related drugs, molecules, and their mechanisms of action, medical experts, geneticists, and biochemists. Identifying those experts within a vast organization can be challenging. But insight engines can analyze thousands of documents and other digital artifacts to see who has experience with relevant projects.

The technology can go further, identifying which experts’ work is connected. If they appear together in a document, interact within a forum, or even communicate significantly via email, an insight engine can see that connection and deduce that the work is related. Companies can then create an “expert graph” of people whose work intersects to build future teams.

This technique can extend beyond the borders of the company, helping to identify the most promising collaboration partners outside the company in a given field, based on publicly available data, such as trial reports, patent filings and reports from previous collaboration projects.

Generate R&D News Alerts

Biopharma companies can also use insight engines to watch for new developments in drug research and stay on top of the latest trends. These news alerts can go beyond typical media sources to include scientific publications, clinical trial reports, and patent filings.

This capability can be used on SharePoint, Documentum, or other sources within a large company to surface relevant information. An insight engine ensures the right information gets to the right people in the right context, and in a timely way.

Optimize Clinical Trials

Clinical trials that stretch over many years generate millions of datasets for every drug and study provide a treasure trove of data. Biostatisticians can ensure they get a comprehensive list of patients having certain diseases within trials on a drug, something nearly impossible with traditional methods.

They can also search and analyze across many drugs and studies, across content and data silos. Over time, this allows biopharmaceutical companies’ growing number of clinical trials to become a valuable asset that can be easily leveraged across a growing number of use cases.

All of these uses can lead to biopharma companies developing new drugs more quickly and getting them to market faster—necessary as these companies face tremendous pressure to innovate quickly and develop new promising drugs as patents for older drugs expire. With insight engines, they can make every part of the journey more efficient, from research, to clinical trials, to regulatory processes, presenting incredible opportunities for everyone in this field.

 

+1Share on LinkedInShare on Twitter

Ferring Pharmaceuticals selects Sinequa and Atos to boost Global Cognitive Search Capabilities for R&D

ferring-logoAs a testament of Sinequa’s fast growing footprint among leading life sciences organizations, we are very excited to announce that Ferring Pharmaceuticals selected Sinequa and Atos to boost its global cognitive search capabilities. Sinequa’s Cognitive Search & Analytics solution was recently deployed at Ferring Pharmaceuticals with Atos as the consulting and integration partner to empower the organization’s Global Pharmaceutical R&D group to look deeply into vast scientific research data sets in order to generate new insights and accelerate innovation

Headquartered in Switzerland, Ferring Pharmaceuticals is a research-driven, specialty biopharmaceutical group active in global markets. A leader in reproductive and maternal health, Ferring has been developing treatments for mothers and babies for over 50 years. Today, over one third of the company’s research and development investment goes towards finding innovative treatments to help mothers and babies, from conception to birth. Ferring has its own operating subsidiaries in nearly 60 countries and markets its products in 110 countries.

In today’s world, especially in the life sciences industry, it is impossible for humans alone to search, process and analyze all the world’s available scientific and research data, Sinequa’s Cognitive Search & Analytics platform  makes this scientific knowledge accessible any time by any given researchers. As Sinequa continues to expand its footprint in this very competitive industry, we are very pleased to count Ferring Pharmaceuticals among our customers. Together with our partner Atos, we are committed to help Ferring improve insights and facilitate innovation.

- Stéphane Kirchacker, vice president Sales, EMEA at Sinequa

test-tubes

Atos, Sinequa’s strategic global premium partner was selected to design, implement, support and operate the platform at Ferring Pharmaceuticals to deliver the highest possible relevancies on search for the R&D teams in different locations.

Sinequa’s solution is bringing the power of AI to Enterprise Search to provide Ferring a “future proof” solution that offers a whole range of opportunities for future innovations. The dilemma of pharmaceuticals is to find the needle in the haystack – scientists need to screen tens of millions of documents from internal and external sources, from structured and unstructured data for identifying relations between genes, drugs, Mechanism of Action (MoA) and finding the right skilled subject matter experts. Other departments like Regulatory & Compliance, Legal & IP, Marketing & Sales, Clinical Trials, HR and more can benefit from customized Search-based applications on the same platform – finding relevant information instantly for fact-based decisions – no waste of time anymore.

-Alex Halbeisen, Expert Sales Big Data & Analytics at Atos

 

+1Share on LinkedInShare on Twitter

Sinequa Wins Best NLP Platform in AI Breakthrough Awards

image001

It’s been a busy few months at Sinequa, and we are ending June on a high note having been selected as the Best Natural Language Processing (NLP) Platform in the AI Breakthrough Awards!

The AI Breakthrough Awards recognize today’s top companies, technologies and products in the artificial intelligence industry. Over 2,500 nominees have participated from all over the world. (more…)

+1Share on LinkedInShare on Twitter

Sinequa’s Big Splash at Bio IT World 2017

PHARMA CONNECTION
Sinequa has taken part for the 4th consecutive year in Bio IT World Conference & Expo on May 23-25 in Boston. We’ve been delighted to meet with our Biopharma and Life Science customers and partners at the show and share innovative use cases of our solution for the Pharma industry via live demos.
Bio IT Demo

“OPEN” LIVE DEMOS

Bio ITBio IT World conference is always for us a great venue to showcase our platform and present how leading biopharma organizations leverage our Cognitive Search & Analytics platform. This year, the attendees were very interested to see how Sinequa combines advanced Search, NLP and Machine Learning capabilities to extract relevant insight from vast structured and unstructured data silos.

 ALEXION’S CONTENT ANALYSIS PROJECT: MINING CONTENT FOR ACTIONABLE INSIGHT WITH SINEQUA

Alexion-Martin-Leach-Bio-IT-2017-SinequaIn our joint talk, our customer Alexion shared a testimonial on the implementation of Sinequa for their content analysis project. The presentation highlighted the technology and approaches they used with advanced data visualizations that help explain information sources. ICYMI – please feel free to get your copy here.

UNLIMITED THEATER PRESENTATIONS

Once again, we were very pleased to see the strong interest of many biopharma professionals toward Sinequa insight platform. Our team gave more than a hundred presentations and live demos in the Sinequa Theater Area where they explained a large panel of use cases including R&D Enterprise Search, Clinical Trial Data Discovery & Exploration, Key Opinion Leaders & Subject Matter Experts… .) BioIT17-Demo-TheaterWe hope you enjoyed the conference as much as we did and you could understand how our Cognitive Search & Analytics platform enable leading pharmaceutical organizations drive innovation, accelerate research and shorten drug Time-to-Market. We are already getting excited for next year’s edition! See you all in spring 2018!

+1Share on LinkedInShare on Twitter