Measure before you build: digital maturity assessment as the first deliverable

Before launching digital transformation projects, you have to know where you are starting from. It sounds obvious enough to skip, and it is skipped all the time. The result is a portfolio of initiatives that each make sense on their own and cannot be integrated with each other: a historian project here, an e-logbook there, a dashboard nobody can feed.

This is part 4 of 9 of the “OT/IT convergence” series; it follows part 3, the implementation steps and continues with part 5, the expected benefits.

Why a maturity model, and which one

A maturity assessment gives you a defensible position on a handful of axes, typically technology, user experience, process optimisation and organisational structure. From that position you can see which initiatives are actually within reach.

Which model you pick matters less than how well it fits. Adopt an existing framework such as the Digital Maturity Model (DMM) or the Digital Plant Maturity Model (DPMM), adapt one, or build your own, but choose something aligned both with the specifics of the industry and with the culture of the company. A model that scores well against a culture the company does not have produces a roadmap nobody will follow.

The five DPMM levels

BioPhorum's Digital Plant Maturity Model classifies plants into five levels of digital maturity. The dividing line that matters most runs between level 2 and level 3.

Plants at level 1 or 2 show little integration between OT and the layers above it: MES, data historians, ERP. Plants at levels 3, 4 and 5 stand out for their high levels of automation, integration and standardisation.

Level 4 plants can analyse data in real time to predict problems and optimise production. Level 5 plants are the "factories of the future": autonomous, self-optimising, and able to connect to other systems plug-and-play. BioPhorum itself presents level 5 as a future concept rather than something plants run today.

In practice, a level 2 plant cannot buy its way to level 4 analytics. What it lacks is the integrated, standardised data collection underneath the predictive model, data people trust. Programmes that invert this order produce impressive dashboards built on data nobody will make a decision with.

Seven phases of assessment

The process below is adapted from the DPMM approach and adjusted against field experience. It is worth following in order.

1. Context and planning

• Obtain executive backing: management support and commitment, in writing.
• Align expectations: every stakeholder understands the purpose of the assessment and how the results will be used.
• Define the stakeholders: IT, OT, business.
• Define objectives: which indicators are actually being sought.
• Choose an assessment framework, adapted to the sector and the company culture.

2. Preparation and preliminary work

• Communicate the initiative and why it matters.
• Brief the teams on the maturity model and the assessment tool.
• Gather what already exists on processes, systems and technologies: a detailed inventory, the architecture, plans and schematics.

3. Assessment

• Self-assessments: representatives from each site or department produce a first evaluation.
• Follow-up meetings and interviews to check and deepen the self-assessments.
• Detailed analysis: score digital maturity against the defined criteria and dimensions.

4. Analysis of results

• Normalise scores so they are comparable and fair across sites and departments.
• Identify trends: which patterns of maturity exist within the company.
• Assess the gaps between where the company sits and its target state.

5. Communication and action

• Share results with all stakeholders, in presentations and a written assessment report.
• Develop a roadmap: a detailed master plan of the initiatives needed to close the gaps.

6. Integration with the overall strategy

• Align with business objectives, so that digital maturity serves the company's strategic goals instead of running beside them.
• Put the money where it raises maturity strategically.

7. Monitoring and updating

• Re-assess at regular intervals to track progress.
• Adjust the strategy to the successive results, to changes in the environment (technological, political, economic) and to the company's own needs.

Two things that decide whether this works

The first is normalisation, which is anything but a formality. Self-assessment across several sites produces data that cannot be compared as it stands. Confident sites under-report problems, cautious sites over-report them, and a site that has just been through an audit scores differently from one that has not. Skip the normalisation step in phase 4 and the comparison between sites measures temperament rather than maturity; the investment decisions that follow will be wrong.

The second is the inventory gathered in phase 2, which often turns out to be the real deliverable. Inventory, architecture, plans and schematics, collected once, properly, and then maintained: that set of documents outlives the assessment. It feeds segmentation design, risk assessment under IEC 62443, patch planning and incident response. Many organisations find afterwards that the maturity score was the least valuable thing the exercise produced.

The part that is easy to lose

Assessing digital maturity is a continuous process that has to be built into long-term strategic planning. A one-off assessment produces a roadmap that starts ageing the day it is presented. The discipline lies in the re-assessment of phase 7, and it is the first thing dropped when the programme gets busy.

Next: the benefits this convergence is expected to deliver, and what they look like in concrete terms.

The DPMM reference is BioPhorum, A Best Practice Guide to Using the BioPhorum Digital Plant Maturity Model and Assessment Tool, May 2020.

References

• BioPhorum, The Digital Plant Maturity Model (DPMM) and Assessment Tool: biophorum.com