1) Check your dictionaries: With careful ongoing maintenance this task will be less daunting, but it is still easy for redundancies and duplications to slip in (especially when combining dictionaries from different sources, such as across sites or from company mergers).  Data chaos is guaranteed if there are multiple representations for the same term.  Clear business rules are needed and should be agreed across teams.

2) Audit your capture and reporting workflows: Are the most appropriate reports being generated or have the business-critical questions changed, rendering reports outdated?  Review the level of context being captured around results.  Check if numbers are being rounded at the correct time.  It is all very well reporting results to 3 significant figures, but rounding numbers prior to storage can lead to a huge loss in precision in downstream calculations.

3) Optimise your queries: As your repositories grow, are your data retrieval queries still running efficiently?  Perhaps your SQL queries could do with some fine tuning or maybe your Warehouse could do with some restructuring.  Two useful books are: ‘Oracle SQL Tuning’ by M. Gurry and ‘Building the Data Warehouse’ by W. Inmon.

4) Work with colleagues to review current processes: Get out there and talk to people from different groups, taking a real interest in their everyday workflows and identifying the slow, mundane steps that they have to repeatedly carry out.  Then assess the impact to prioritise tasks, remembering that sometimes perceived impact can be quite different from actual impact.

5) Stay up to date with current technologies: Attending conferences and reading literature is time well spent if it means identifying a new technology that improves processes.  For example, check out the O’Reilly Radar blog or attend the Science and Information Conference.

Like a backlog of household chores, if all of the above seems overwhelming then why not get in an extra pair of helping hands, such as Amethyst, to help you sort through the mountain of clutter and prioritise your clear-up strategies.  Sometimes all it takes is a fresh pair of eyes to ask the questions that need to be answered in order to polish up your processes.  After applying the above techniques you will spend less time on manual error-prone steps and have more efficient processes and better quality data, therefore maximising your chances of making successful business-critical decisions.

This article discusses how Funnel Diagrams can be used to make a positive impact on your lead optimisation projects.

Topics include: spotting process bottlenecks, confirming the successful impact of process changes, gaining insights into how achievable a goal is, taking a glance at how resources are split across multiple projects and assessing resource needs.

Two example lead optimisation projects that are at different stages are used to illustrate the funnel applications. An error bar extension to the original visualisation is presented.

Hirons L. Chemistry Today, August 2012, 30(4), 24 – 26

Funnel Diagram for project A:

Funnel Diagram for project B with Assay 1 error bars:

Hirons L, Johnstone C, Sambrook-Smith C. Drug Discovery World Winter 2011/12, 13(1), 44 – 49

A single funnel is shown to the right. Each rectangle represents an event. Rectangle width
represents the number of compounds processed by that event. The distance between a rectangle
and the top of the funnel represents the average number of days from compound registration to completion.

Attrition is therefore represented by changes in a funnel’s width and time by elongation of a funnel

Below is a funnel diagram that gives a six-month snapshot of a lead optimisation project. Each funnel represents a month
with a trellis of 6 funnels giving a summary of how processes are changing.

Highlights from the above diagram:

• Changes in the number of new compounds can be seen by glancing across the red rectangles. The sudden change between
  May and June relates to the addition of chemistry resource.
• In July the funnel folded back upon itself indicating an unexpected order of events
• Assays 1 and 2 are consistently completed within a week of compound registration, regardless of the volume of requests – indicating a minimal impact area for process improvements
• Variable timelines are seen for Assay 3, independent of throughput – an area to examine further