Improving R&D workflows

Workflow automation is an established approach to drive business efficiency and productivity, but formalising and automating workflows in R&D is often more challenging than in other business functions. The innovation and creativity required in R&D means that it can be difficult to capture well defined processes. The emergence of new standards, mature tools and technologies, combined with the increasing body of workflow best practice means that R&D organisations now have the opportunity to automate workflow and realise efficiency and productivity gains. Successful delivery, however, requires experience and expertise to identify where maximum benefit will be realised without compromising the creative flexibility required by an R&D organisation.

The opportunity

Workflows are ubiquitous in R&D, from data analysis pipelines of individual scientists or technicians to end-to-end product development processes that deliver an R&D organisation’s core purpose. Small and large, these processes are the heartbeat of business and each provides opportunities for increased efficiency and effectiveness.

What makes R&D different

In some domains, such as commerce or insurance claims processing, processes can be standardised and automated relatively simply because “business as usual” can be easily defined. R&D is different in ways that make the benefits of workflow harder to achieve:

  • R&D often requires novel solutions to new problems, which
    in turn require creativity and innovation that cannot easily
    be captured within a process model.
  • A rare mixture of technical analysis skills and substantial
    domain knowledge is required to elicit, understand and
    exploit the business processes within R&D organisations.
  • There are often conflicting goals or constraints between
    vertical research areas and horizontal operations. This
    makes it difficult to capture or agree a single process that
    spans these divides.
  • Finally, integrating the human element: scientists thrive on
    freedom and flexibility.

New standards

Recent developments have made it easier to automate R&D workflows. Standard methodologies and modelling formats, such as BPMN and BPEL, have become widely adopted. This in turn makes it easier for practitioners to develop deep expertise in modelling approaches. Likewise tools that generate or consume workflow models are easier to integrate using common standards and formats. This simplification of the task of creating workflows and delivering software to exploit them means that more focus can be given to the domain under examination, which is necessary when working in complex domains such as those associated with R&D.

The recipe for workflow success
When exploring the possibilities workflow offers, either for the first time or returning to it after previous failed attempts, the options and possibilities can be bewildering. Identifying the best way forward requires a combined knowledge of a particular industry, workflow standards and technologies, and R&D sensibilities.

The first step should always be to review the processes and workflows that currently exist and identify the improvements and technologies that will provide the most significant and immediate benefit at the lowest possible risk. This initial phase requires information from several parallel streams of analysis work:

  • Elicit and model existing processes.
  • Capture and visualise workflow data.
  • Analyse, rationalise and improve processes.
  • Develop workflow improvement and implementation
    strategies.
  • Analyse the support of enterprise SOA for workflow
    systems.

In some cases this analysis will reveal alternative approaches to be more appropriate or that the costs and risks of change are too high and so no action is the best option.

Technology and Consulting

© Copyright 2017 Tessella
All rights reserved