Get Ready For Recruiting Automation Strike Teams

Emerging technologies such as robotic process automation (RPA), virtual agents, and machine learning — these are those invisible robots described in the recently published Forrester book "Invisible Robots in the Quiet of the Night: How AI and Automation Will Restructure the Workforce." Invisible robots have rocketed automation to a top spot among enterprise initiatives, yet firms are dragging organizational and governance issues along as an afterthought.

To address these gaps, automation “strike teams” are emerging. So what are they? Strike teams replace the automation center or center of excellence concept. This well-worn phrasing or description has two drawbacks when applied to today’s automation initiatives: First, the term “center” implies more control (and, hence, bureaucracy and tardiness) than automation initiatives can withstand that are inherently federated, distributed, and centered in the business; and secondly, the term “center” implies a single instance, whereas we are seeing multiple strike teams forming that may specialize in a domain — for example, operations (for RPA) or conversational intelligence for B2E or B2C use cases.

Strike teams are a reaction to these realities:

  • The road to automation is paved with islands. Often, different groups in organizations set up their own automation technology, along with governance and best practices, leading to duplication and automation sprawl.
  • Bottom-up deployment prevents scale and leads to governance nightmares. The business is directly adopting emerging automation technologies like RPA, chatbots for virtual agents, and decision-making processes driven by machine learning. Needed controls for security, business continuity, documentation and, increasingly, explainability are often afterthoughts. Lack of a formalized operating model coordinated by automation teams slows scale. For example, 52% of enterprises with RPA deployments are stuck with fewer than 10 robots in production.
  • Required federated operating models develop slowly. Developing algorithms to make critical business decisions or building digital workers that emulate human activity requires knowledge that resides only with the business. New operating models support this federation by defining, for example, what IT support means and how to distribute it in new territory.

What The Automation Strike Team Does

Automation strike teams address the growing federation of business and traditional technology management expertise. Many organizations will have more than one, and each team may specialize in business or technology domains. Here is a summary of what they do:

  • Evangelize automation’s potential. The best teams will be the driving force for automation. These teams work with domain experts to perform process analysis and design and deliver automation. Strategy, planning, explaining, presenting, and championing are all key responsibilities. The automation team will serve more than one set of stakeholders if the groups should be employing similar technologies.
  • Create and manage guardrails for deployment and execution. Distributed responsibility puts emphasis on maintaining best practices before automation moves into production. Automation design within business areas makes this a crucial factor.
  • Provide design authority on what to automate. Business departments need assistance to determine what processes are good ones to automate and what technology is best.
  • Drive architecture decisions with knowledgeable subject-matter experts (SMEs). While domain experts will be heavily invested in automation design, testing, and maintenance, scaling out automation requires architectural guidance. Automation strike teams have the top automation SMEs in their organizations, and they provide significant tool and process expertise.
  • Coordinate across islands of automation. Automation requires that many providers, platforms, and emerging technologies work together. For example, chatbots will need to get help from text mining, RPA digital workers, and decision management driven by machine learning. Vendor platforms are developing to provide orchestration and management across different types of automation.
  • Jump-start new projects. Teams must smooth out templates, licenses, and provisioning of software tools and expertise to move automation forward. Initial support of automation is critical.

Craig Le Clair, vice president and principal analyst at Forrester wrote this article, which can also be found here

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of HR&DigitalTrends.