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Implementing Electronic Lab Notebooks
How do you define and manage success?

Introduction
In the past five years, the electronic lab notebook (ELN) has moved from nascent technology deployed mainly by early adopters and technology enthusiasts to a mainstream laboratory chemical informatics platform. Atrium Research and Consulting estimates that over 25% of the potential market for ELNs has either deployed or is in the midst of deploying an ELN, with larger organizations of over 500 users comprising the bulk of these deployments.1

The deployment of an ELN has a transformational effect on the way research is performed. As such, plans to deploy an ELN must address the needs of scientists who create experiments, groups and departments that make use of the experiments and data created by scientists and business sponsors who finance the projects. These groups may see the goals and success criteria for the project differently. Technical sponsors generally look at factors that make scientists more efficient in documenting experiments. Business sponsors tend to focus on streamlining system costs and lower total cost of ownership.

What makes an ELN implementation successful?
The answer varies depending on who you ask and how they define success. Understanding the different needs and expectations of the stakeholders can help you make the best case for implementing an ELN.

The demands of the technical side are somewhat straightforward. Scientists and technical managers ultimately want to do their jobs faster, with as little disruption as possible. A successful ELN implementation lets scientists quickly create and edit experiments and, more importantly, share and reuse experiments they or others have created. Integration with applications essential to their work—registration, metrology, LIMS, and inventory systems—results in less time spent cutting and pasting results. Technical managers gain visibility into research to track experiments in progress and gauge efficiency. And both groups should be able to use the ELN without extensive training or support.

The business case for an ELN, however, can be harder to make. Business sponsors view ELN deployment as an investment intended to improve R&D efforts and process efficiency. Thus success is measured by return on investment (ROI), the measure of money in (expenses) vs money out (savings) over a specified period of time.

Expenses in an ELN implementation include not just the cost of purchasing hardware and software, but configuring systems, training users, and maintaining systems over time (often referred to as total cost of ownership). Savings are easy to identify, but may be harder to quantify. Factors influencing ROI include:

  • Project efficiency (“Are we conducting more experiments”)
  • Scientific efficiency (“Am I spending more time doing science and less on cutting and pasting data into my notebook?”)
  • Cycle time within projects (“How quickly are we submitting samples or passing work to the next stage?”)
  • Rework (“How often are we repeating or duplicating experiments?”)
  • Information gathering processes (“Is it easier to review research or collect information for intellectual property and regulatory filings?”)
  • Systems used (“Has the implementation enabled us to consolidate or decommission systems?”)
  • Time (“Are we able to initiate any of the above activities faster?”)

Obviously, business sponsors define success by how well an implementation minimizes expenses while maximizing savings, as well as the time factor (savings today are more valuable than savings tomorrow). Organizations can make a business case for an ELN by looking for streamlined configurations, support for critical document and scientific workflows, cost-effective outsourcing options, integration with or elimination of existing systems, and strategies for achieving lower total costs of ownership.

Managing Success

fig1
 Fig 1: Core areas in an ELN deployment
Though the measure of success for an ELN deployment project can be measured by ROI, business and technical sponsors will have different opinions about what factors impact ROI the most. But both camps will agree that monitoring the impact of ROI factors through five core areas will have the greatest influence on overall project success and ultimately ROI valuation.

Foundation This area focuses on evaluating and preparing the general environment within the research organization. Work in this area is primarily concerned with ensuring that the ELN is deployed to the optimal groups with minimal disruption to overall organization. Work also focuses on harmonizing scientific workflows and making sure the needs of auxiliary groups, (e.g.: archivists and legal) are met with the ELN deployment.

Experiment Documentation This second layer focuses on evaluating how individual disciplines (e.g., process chemistry, analytical chemistry, or discovery) work to create and document experiments. Analysis focuses on creating and optimizing the ELN to accommodate the scientific workflow associated with creating and documenting experiments.

Inter-Department Collaborative Work The third area looks at how different groups within the organization can maximize collaborative activities and gain research efficiency. For instance, studies might investigate the movement of samples and analytical results between process or development groups and corresponding analytical/characterization laboratories.

System Integration Although the ELN can have a transformative effect on research operations, it is only a single component of an overarching electronic lab environment within the research organization. The work associated with this fourth area focuses on how to integrate the ELN with other informatics systems such as LIMS, CDMS, etc. to obtain multiplicative benefits. Research Management. The top of the pyramid focuses not on the creation of experiments in the ELN but the metadata generated in the ELN system as experiments are created and managed. Typical metadata includes:

  • Number of experiments created
  • Average time to complete an experiment (creation to witnessed date)
  • Name/number of scientists creating experiments

Although this information is useful in and of itself, it can become even more beneficial when combined with experiment data such as:

  • Target Compound
  • Department
  • Development Phase

The intersection of these data provides valuable insight into the research activities, helping to answer questions such as:

  • How many experiments did it take to complete a formulation of compound A?
  • How many scientists were involved in developing compound A?
  • How long did it take to complete the process development stage for compound A?

The effort to collect this data is minimal. The value of the mined data in evaluating ongoing work and planning new projects can be invaluable.

Summary
This article presents an overview of the success factors the business and technical stakeholders use when evaluating the success of an ELN deployment project and the impact on ROI. The five- tier approach provides a methodology that evaluates, prioritizes and manages these factors to ensure a successful ELN deployment.

In future articles I will explore in more detail the application of each tier to the definition and management of a successful ELN implementation.

References 
1) Elliot, Michael H., “Electronic Laboratory Notebooks Enter Mainstream Informatics” Scientific Computing http://www.scientificcomputing.com/Electronic-Laboratory-Notebooks-Enter-Mainstream-Informatics.aspx?terms=ELN

Bennett Lass is the Director of ELN Services at Accelrys Inc. He may be reached at editor@ScientificComputing.com.
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