5 Critical Parameters in Dealing with PLM Complexity

Lionel Grealou Data, Engineering Leave a Comment


Conventional planning implies that organizations are largely predictable enterprises and that they are typically resistant to change. These are characteristics of linear systems; therefore, conventional planning ignores non-linear characteristics of organizations. In organizations, including manufacturing companies, many relationships are non-linear. In complex New Product Development (NPD), causal links between actions and outcomes are weak despite documented processes and innovation frameworks. As a matter of fact, design and engineering rely on people’s creativity and tacit knowledge, and often principle of ‘agile‘ non-linear project management apply. Engineering outcomes are hard to predict as they rely on a wide array of factors and parameters, requiring extensive market and Engineering Research and Development (R&D), open innovation, cross-silos and cross-disciplinary integration, etc.

Product Development is often managed on the ‘edge of chaos‘. Product Life-cycle Management (PLM) solutions are providing a constant ‘system‘ in enabling process and system stability for effective collaboration, innovation, learning and social integration. PLM offers alternative framework for understanding social systems along the line of the following critical parameters:

  1. Adaptive behavior: required to succeed at the edge of chaos; governance is a mean, not an end; process documentation is an essential deliverable, but it needs to be lean, i.e. not every business activity require formal processes (…)
  2. Self-organization: key to survival under volatile conditions, opposite of hierarchically imposed change, transformation from within.
  3. Learning: need to ‘unlearn’ to escape dominant logic, maintain a balance between positive and negative feedback (adopt double loop learning).
  4. Processes and structures: adoption is most effective in partially connected processes and structures.
  5. Make change part of the culture: time pacing not event pacing, continuous performance measurement, ongoing small changes as part of routine business as usual, roughly right (don’t expert perfection or right first time each time), realigned over time (continuous improvement).

Competitive success factors in dealing with complexity include an ‘agile‘ and open business change mindset with an appetite for risk management (rather than issue management), often coupled with culture change management (medium/long term perspective):

  • Focus on share of future opportunities rather market share;
  • Emphasis on integrated systems and competencies;
  • Perseverance;
  • Business critical continuous engagement; and
  • Acceptance of lack of (or changing) structure.

This is re-enforced by the fact that most complex PLM requirements are often discovered or elaborated ‘on the fly‘ during implementations (typically, ‘God is in the detail‘). Technical skills and experience are mandatory, but not sufficient to ensure PLM success.

Robust delivery models must be put in place to ensure that the scope is controlled in an agile manner (iterations), time-bound (defined resources and budget), with the relevant ‘ no change window‘ and enabling deployment ‘acceleration‘.

Hence, the importance to understand late design issues and impacts through informed change management.

What are your thoughts?


This post was originally published on LinkedIn on 25 August 2015.