Samen met onze Cordence Worldwide partners helpen wij organisaties wereldwijd bij het bereiken van hun doelstellingen op het gebied van digitale transformatie en organisatieverandering. Onlangs hebben wij een internationele bijeenkomst georganiseerd samen met vertegenwoordigers van Vervoerregio Amsterdam, RATP (openbaar vervoerbedrijf van Parijs), Danske Statsbaner en ProRail om te praten over de impact van data gedreven beleid en besluitvorming op hun bedrijfsvoering.
De samenvatting van deze derde internationale bijeenkomst vind je hieronder. De belangrijkste conclusies zijn: investeer in een lange termijn (onderhouds)programmering voor je assets zodat je ver vooruit kunt kijken, neem de verwachtingen van de politiek en eindgebruikers mee in de besluitvorming en investeer in een nieuwe werkcultuur door het personeel onderdeel te laten zijn van de nieuwe manier van werken.
Implementing, structuring, and managing data for automation/infrastructure can be a challenge. Despite the challenge, many organizations want to transform their traditional infrastructure organization into a data-driven organization. They do so because of an ambition to progress from planned to predictive maintenance, to take advantage of new technologies, such as drones and sensors, or simply because of budget cuts. It requires to not only change the way the work is organized, but also the way data is collected and used.
Cordence Worldwide member firms are helping organizations around the world achieve their goals in digital transformation. In November 2021, we hosted the third International Peer Roundtable with leaders from transportation organizations to discuss asset management impacts on their respective systems. Participants included the Vervoerregio Amsterdam (Transport Authority Amsterdam, the Netherlands), RATP (public transport operator and maintainer from Paris, France), Danske Statsbaner (or Danish National Rail (DSB)) and ProRail (Dutch rail infrastructure organization). This meeting was a joint effort of the Cordence Worldwide Asset Management team (TwynstraGudde, North Highland, Oresys and Valcon).
Clients were invited to share insights on the combined possibilities of digitalization and asset management for their respective organizations. The facilitated discussion triggered robust discussions on data driven policy and decision making. The key takeaways from the Roundtable are:
How to predict future degradation and prioritize maintenance, was one of the key questions. Several of the participants spoke about the value of Predictive Modeling for Asset Management planning. The benefits for this approach are focused on long term planning and the models being used to plan for the 7-10 investment period based on data captured and modelled for the 0-5 yrs horizon. One of the challenges shared is to be able to collect enough and relevant data on existing assets in order to predict future degradation with data science methods.
One of the speakers spoke about the increasing challenges of extending maintenance windows where these have to be internally and externally negotiated. (A maintenance window is a prescheduled time when a system can be taken offline for maintenance.) Especially in new infrastructure projects, the speakers agreed on the importance of taking Asset Management demands and requirements into account as early as possible to agree and set the minimal time necessary for maintenance. If not done properly, the ability to design in optimal methods to maintain the assets has been missed – resulting in very short and expensive maintenance windows and little support from society/end users.
Politics and customer expectations can make it hard to change a schedule once set. Justifying the changes financially is easier to provide than changing the expectations of customers whilst not impacting satisfaction of the services provided. Coherent external communications are a key element in gaining acceptance of changes and maintaining customer perception and satisfaction.
The discussion centered on the challenges faced with breaking down historic siloed working practices in the use of predictive asset management. Large cultural shifts in the workforce is required to accept new working practices. One example is the cultural shift from the maintenance centered on specific equipment to a systematic view of maintenance. There will be necessary changes at management level when an organization is built around ‘functional units’ that manage only a part of the system to looking at it in this new way.
The speakers agreed on the importance of strong change management and involving the workforce and end users in the change process to strengthen engagement and reduce the period of insecurity during which resistance is developed. For example, involvement in defining requirements and analytics. In order to successfully include workers, there needs to be clear governance and management of priorities, as well as a culture to support change.
Wil je van gedachte wisselen wat data gedreven asset management voor jouw organisatie betekent? Laat het mij weten. Ik praat er graag met je over door.
Lees ook de samenvattingen van de andere internationale bijeenkomsten: