Introducing Workflows: for scientists to move R&D forward, together

Trey Miller

The potential for collaboration

The Benchling team has always believed that easy-to-use, scientifically-aware software has the potential to unlock the power of biotechnology. We’ve built a powerful platform of applications that R&D organizations around the world rely on everyday, but we had a hunch that we could further improve how they use Benchling to bring the right people, materials, and data together at the right time.

Working with a wide range of customers from across biotech, we realized that many of our customers struggled to collaborate effectively. To understand it better, we studied and deconstructed a wide-range of workflows, and heard similar themes. Communication and coordination broke down as teams became more specialized and distributed. Sample and data handoffs became inefficient and error-prone. And it became increasingly difficult to understand and orchestrate long-running efforts. Collaboration became a chore rather than an advantage.

We knew solving this problem demanded a new approach R&D teams need software designed for collaboration - empowering them to cut through the noise and reach the ideal outcome more quickly. That’s why we’re excited to introduce Benchling Workflows.

Workflows orchestrates processes efficiently

You can think about Benchling Workflows as the engine that drives the people, materials, and data through the rich, domain-specific Benchling applications. Workflows offers the ability to plan and execute complex, interdependent tasks efficiently and collaboratively for work done in study management, process development, sample and inventory management, and quality controls.

And it’s much more than typical project management software. Rather than passively reporting what’s happened, Workflows directs teams through Benchling applications where they already work to automatically record progress and status updates in real-time.

Managing scientific tasks with flowcharts

Our product model is centered around tasks. These represent a job-to-be-done like performing an analytical test on a sample, producing a new lot of media, passaging a cell line, or purifying an in-process sample. Tasks standardize the way we think about work: a task is assigned to a scientist, scheduled, and executed to create new data or results.

We use tasks to build the graph of an end-to-end workflow that we call a flowchart. This adds sequence and orchestration to tasks while automatically propagating data and materials between them. And everything is composable: after defining a task once, you can use it to build many different flowcharts.

This means the team who produces new lots of media can keep track of a single queue: direct requests for media, media required for cell culture, and media needed for viral production are all just media prep tasks. Scientists can then aggregate and execute these tasks in the most efficient way by finding those with the highest priority, due date, or grouping them by the type of recipe.

workflows screenshot


R&D teams using Workflows have shared how the product transforms how they work as an organization. These benefits rolling up into three common themes:

Increased productivity - Teamwork now happens within a shared system that delivers scientific context and up-to-date status tracking. Scientists can more easily find what they need to do.

Increased velocity - Handoffs are a natural part of the collaborative workflow rather than a separate effort of emailing, scheduling meetings, and sharing files. Managers are also able to clear hurdles and refine processes to reach milestones faster.

Increased visibility - Now experimental, analytical, and process results are aggregated to surface key operational and scientific insights.

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