As new technologies continue to emerge, many businesses have transformation programmes in place to keep pace with innovation. Run by experienced project managers, these programmes are often driven by change management processes and are focused on outcomes.
But is this the best approach for long-term success? Firms should consider how technical skillsets can be leveraged to manage the interactions between people, components and solutions to embed workable and lasting operating models and facilitate enterprise innovation.
The glue that holds transformation programmes together
Establishing an effectively run organisation is one of the age-old challenges of business and it doesn’t happen by chance. An organisation is made up of many functions and component parts, which are carefully nurtured to support the business as a whole (marketing, sales, finance, operations, IT, analytics etc). But during change programmes, the interactions between these functions can be overlooked, or are simply reviewed in terms of immediate project outcomes, rather than supporting long-term collaboration. As a natural consequence of this, when things go wrong, there can be a tendency to blame one function or another, rather than looking at systemic pitfalls in the connections between them.
An effective transformation programme should actively establish an operating model to act as a glue between functions, identify areas of risk, and make changes sustainable.
The tendency to focus on tangible deliverables
One of the main reasons change programmes focus on immediate outcomes is because they have tangible milestones for success. It is always easier to discuss and manage a new software rollout, or the skills needed for a certain function, than the less tangible ‘spaces’ between them, such as the ongoing services to support that software, the relationships between suppliers, or the processes and culture necessary to suitably react to customer feedback. But there are other reasons too, such as:
Lack of terminology
In technology, there are terminologies for managing the interactions between functions, such as 'data transfer' or 'Application Programming Interfaces (APIs)', and the need for the interaction to be managed is well understood. This is demonstrated by the API economy, but the lexicon for the interaction between business functions is comparatively weak.
It’s fairly easy to identify and explain the need for an expert in a certain field, such as law, accounts, marketing or strategy. It’s not so easy to find people who know about how those fields interact or experts in the handoffs between them.
There isn’t often an organisational owner of these handoffs because of how accountability boundaries are drawn. By nature, interaction depends on both parties who co-own, or in some circumstances avoid, this responsibility – and at least have to jointly agree any changes.
The politics of accountability
It can be difficult to manage competing viewpoints, priorities and approaches to reach a good outcome. Essentially, it comes down to managing the politics of accountability, which is difficult to do with overstretched resources. This is particularly important for engaging and leveraging business control functions through change, especially around regulatory or risk practice.
The time available for post-implementation support
In the past, it was possible to have an extended post-implementation period to help embed change by supporting a handover to business as usual (BAU). This developed the interaction between key operational teams, but the speed and continuous nature of change means that this level of post-implementation support is costly and relationships need to be in place prior to implementation.
Addressing these issues can help establish an operating model that connects each business function, emphasizes a dynamic culture with empathy and understanding, and continues to drive the business forward.
The role of an operating model in transformation
The key reason an operating model is so important is because organisations aren’t static and business activities constantly evolve. Firms that don’t understand how each function interacts can struggle to identify the cause of operational issues and may find it difficult to fix them. An operating model outlines how the organisation works and can help to identify effective means of changing it.
The current interest in AI and machine learning is a good example of how these operating models work in practice. Algorithms create a model of how a situation works, then constantly update the model based on feedback on what worked and what didn’t. The model, the delivery, and the feedback loop are constantly evolving for value delivery.
Supporting your project manager
Typically, organisations expect project managers to set up these relationships for long-term success, but this doesn’t always play well with their skillsets, which are often change management and delivery methods. Project managers usually lack technical expertise related to the change project at hand, but are usually the dominant person in driving the transformation programme forward. This increases project risk, making it difficult to identify potential pitfalls and set the organisation up for continued success, once the change project structure is disbanded.
These issues can be addressed through enterprise teams drawing equally on both project management and subject matter expertise. Technical roles, with a strong knowledge of content, can be assigned to manage the interactions between people, components and solutions. This can help to establish lasting relationships and embed realistic, workable operating models and workflows to support the transformation.
For more information on how our transformation team can help you, get in touch with Neil Furnivall.