smartlogic webinar - arnold_duckworth - oct14

Improve Knowledge Management from Developmentto Manufacturing with Content Intelligence

Who’s speaking today?

Adam DuckworthAssociate Director,

MMD Knowledge Management COEMerck, Inc.

Douglas ArnoldDirector, Account Manager of

Knowledge Management, MMD Information Technology

Merck, Inc.

Anne LapkinSVP Global Strategy

Smartlogic, Inc.

Agenda

A bit about Smartlogic

A bit about Merck

Merck challenges

Merck solutions

The outcome

What is content intelligence?

Questions?

A bit about Smartlogic

We believe there is huge business value locked away in content and that organizations that manage to unlock that value can outperform others, because the majority of the enterprise’s intelligence is contained in that content. It augments the value most organizations have already found in structured data.

To realize this value we know you must understand your content, the information and knowledge it contains, how it can be applied in the context of your operations and how it enhances the insights from structured data. The content must be described completely and consistently with metadata.

We focus all our energy on creating value from unstructured content – something we call Content Intelligence

Jeremy Bentley, CEO

Through 2015 organizations integrating high value, diverse, new information types and sources into a coherent information management infrastructure will outperform their industry peers financially by more than 20%

Gartner

“

Content intelligence is…

Content Intelligence is the combination of semantic technology and information science that allows machines to model, interpret, describe, analyze and visualize the content of the enterprise in order to leverage the human intelligence locked in that content.

A bit about Merck

Key Company Facts

6

$7.1 billion; 22 products in late-stage development; key areas: oncology, CV, diabetes, respiratory & immunology, neurology, infectious disease and vaccines

2013 R&D

EXPENSE

More than 100 significant licensing and partnership deals were completed in 2012 and 2013

EXTERNAL LICENSING

$44 billion; 59% of sales come from outside the United States

2013 REVENUES

Pharmaceuticals, Vaccines, Biologics and Animal Health

BUSINESSES

Whitehouse Station, New Jersey, U.S.A.HEADQUARTERS

Operating since 1851RICH HISTORY

Known as Merck in the United States and Canada, and MSD elsewhere

WHO WE ARE

Approximately 73,000 worldwide (as of 6/30/14)

EMPLOYEES

The business challenge

The business challenge

Dimensions of the problem

Knowledge Flow Analysis

Identified gaps in the flow of small molecule product

technical knowledge

Proc

ess

Step

Know

ledg

e N

eede

d

Crea

ted

By

Use

d By

Expl

icit

or

Taci

t

Whe

re is

it

Flow

Impa

ct

Gap

/

Opp

ortu

nity

ExplicitDocument Repository

None

TacitPartially captured on RA

Rationale not consistently captured

BSafe operating

conditionsSafety Eng API Engineering Explicit

Document Repository

Not sure which is latest version

CSummary of lab

developmentAnalytical

Registration Team

ExplicitLocal team work space

No standard repository

DPerformance of similar product

Manufacturing Development TacitLocal, at manufacturing sites

Limited access to SMEs and no standard expectations for reporting

EKnowledge on

powder processing

Pharm Engineering,

ManufacturingManufacturing Tacit Unknown

No formal SME listing identified

AEarly Risk

AssessmentAPI Engineering

Pharm Engineering

VOC• Difficult to locate knowledge

• No common defined standards

• Organization of knowledge varies by area/location

• Technical packages can take weeks to months to assemble

• Inconsistent quality of information

• Difficult to identify current version

• No common repositories

• Knowledge stored locally

• Very limited access to key content

• Moving knowledge between repositories is low-value work

• Lack of context & rationale

“In manufacturing, we make two products: clinical/commercial supplies and knowledge

Classifying 2,000,000 historical documents manually would take 30 person years

The business challenge

The solution

Product Knowledge

Technical Knowledge System

Content Intelligence

And the survey says…

Flexible; Shift to Value

Knowledge Seeking

Efficiency and Productivity

Avoiding Rework

Content intelligence is…

Content Intelligence is the combination of semantic technology and information science that allows machines to model, interpret, describe, analyze and visualize the content of the enterprise in order to leverage the human intelligence locked in that content.

Semaphore in a nutshell

Assisted and automated metadata enrichment Resource Description & Authoring

Content Editors

Contextual metadata driven search and navigation

Portal Users

Knowledge Discovery & Surfacing

Information Scientists Business Analysts

Subject Matter Experts

Design and collaborative enrichment of ontologiesSemantic Modelling

• Authoritative content centralized - “single source of truth”

• Knowledge workers no longer waste time finding or re-creating information

• Eliminate intense manual resources for processing, classifying and tagging historical content ($2.4M savings)

• Expected payback expected within one and a half years

In summary

Recommendations:• Focus on people, process, content, and technology• A journey with multiple stages• Don’t over engineer it• Automate

Questions?

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