How Organizational Gaps Can Cripple Your Digital Manufacturing Efforts

Digital Manufacturing Efforts

Table of Contents

In my previous blog, I spoke to the Technical issues that I often see impacting Digital Manufacturing projects.  But as Sight Machine’s lead for Digital Transformation efforts, I’ve discovered that while ensuring you have machine connectivity in place, a well thought out cloud & security policy, and a plan for how manufacturing data will be used are all key foundational capabilities, in the end, they don’t really matter.

What I mean is, of course they are important, but not having them in place tends to just slow down initiatives.

On the other hand, not having the proper organizational capabilities in place can ‘kill’ a project.

By their nature, digital transformation projects rewire existing processes and lines of communications in manufacturing organizations. I’ve seen numerous projects die on the vine or get stuck in cycles of endless pilots because the key organizational capabilities required for success and scale are never addressed.

I’ve found three areas of Organizational Readiness that are most critical to project success: (1) Commitment & Budget; (2) Skills & Resourcing: and (3) Change Management.

Commitment & Budget

The most important factor I’ve seen impact the success of a Digital Manufacturing projects is the level of buy-in it has across different levels of the organization.  Too often, projects are ‘pushed’ by the corporate innovation teams without alignment from the local plant.  Or, just as crippling, initiatives are driven by an innovative plant leader who does not have the resources to scale the innovation across the Enterprise.

But align between these two groups is just the start.  Truly successful projects require align not just from corporate and plant leadership, but also IT, operational teams, and even machine operators.  Manufacturers need to spend more time up front articulating a vision for where there enterprise is going, and how these projects support that long-term roadmap.  And seeing various organizations align resources and budget to support the project is a key gauge for knowing if the project has a chance.  Some of the checklist items I look for upfront on a project are:

  • Is Data-driven decision-making a critical priority and has budget allocated
  • Is on-site plant leadership committed to the project, and is there align on scope/objectives with corporate innovation teams
  • Is IT aligned to support the project

Skills & Resourcing

One reason why ‘Commitment’ is so important is that it helps ensure the right resources and skills are allocated to support the project.  The unique attribute of a Digital Manufacturing project, is that it requires a mixture of different capabilities to come together.  The value of these efforts results from combining the subject matter expertise of machine data, IT systems, data science, and operational processes.  Some of the key resources I’ve found that must be involved include:

  • Manufacturing experts who understand the available data and physical sensor structure
  • IT staff who can connect sensors to networks and data storage and develop applications for the plant floor
  • Data scientists who can interpret and draw insights using manufacturing data analytics tools

Change Management

To capture the valuable opportunities identified by analytics, manufacturers need to ensure the right resources are in place to implement the identified process, staff and product changes.  I’ve seen numerous manufacturers invest significantly in the IT systems and services required to build data-driven decision making capability, but then never invest in the capability to operationalize that capability.  Metrics, incentives, and processes all need to be re-evaluated in light of the new data capabilities the project delivers.  Some of the key attributes I look for in organizations to determine how likely the project is to be successful in the long run are:

  • Are there clearly established, measurable KPIs aligned across facilities and assets.
  • Is the right leadership in place to implement process, staffing, and production changes to capture the value identified by analytics


It’s important to note that organizational readiness is not a binary measurement – few organizations will have all of the right attributes in place for successful projects.  Its critical for manufacturers to recognize the important role organizational attributes play in long-term project success and begin discussions about how the odds of project success can be increased by evaluating organizational gaps.

At Sight Machine, we’ve packaged our learnings on the Organizational capabilities required for successful projects into our Digital Readiness Index (DRI).  This assessment tool enables manufacturers to evaluate which plants have the organizational assets and buy-in they need for an initiative to succeed. Understanding where individual plants sit in terms of these readiness attributes allows companies to select the appropriate use cases that will more readily deliver value.

Picture of Sudhir Arni

Sudhir Arni

Senior Vice President, Business Outcomes at Sight Machine In this role, Sudhir leads a team of transformation leaders responsible for on-boarding all new customers and customer success managers who ensure adoption of Sight Machine technology across the global enterprise customer base enabling business expansion from existing customers

Curious about how we can help? 
Schedule a chat about your data and transformation needs.