Written by
Changeboard Team

Published
16 Mar 2011

Whirlwind tour to higher organisational effectiveness

16 Mar 2011 • by Changeboard Team

What is professional discipline?

Until recently, intangible knowledge professions like data management, change management and business analysis have been loosely defined and have often fallen through the cracks between business and functions.

There's a better way of managing these professions: building organisational capability around them, which we call professional discipline. This organisational capability embodies best practice from traditional functional teams and innovative communities of practice, ensuring the provision of critical skills, improved learning and consistent service delivery. With this article, the London Business School’s Human Capital Network begins its organisational effectiveness series of publications.

The pressure is particularly high in asset-intensive industries, such as pharma and oil & gas, due to associated business critical risks, such as in data management, that come with making wrong decisions based on incorrect data.

These knowledge-intensive professions face the renewed Challenge of managing for Results, i.e. managing the intangible knowledge-intensive assets they produce in a way that grows associated revenue while reducing the associated cost. We find that the effective management of those assets is dependent on the organisational capability to support them, which we call professional discipline.

Functional teams and communities of practice

Organisational forms for knowledge-intensive professions

Professions like data management, change management and business analysis manage explicit and tacit knowledge. Explicit knowledge is the knowledge of what to do. It's codified into words and so is easily transferrable. In contrast, tacit knowledge is knowledge of how to do it. Tacit knowledge cannot easily be put into words, takes time and considerable investment to develop and is transferrable mainly in the process of social interaction.

In recent years, many companies have adopted a range of practices and organisational forms to facilitate explicit knowledge flows, such as information technology projects (like portals, intranets and group decision support systems) and functional teams (e.g. business change teams). Communities of practice, on the other hand, have been adopted to share tacit knowledge.

Functional teams are driven by deliverables with shared goals, milestones and Results. Team members share and exchange information and experiences in a similar way to a community, but team membership is defined by task. Teams typically have designated members who remain consistent in their roles for as long as the roles are relevant to the organisation, and the teams are dissolved once the mission is accomplished. Teams are therefore more rigid and hierarchical, yet they focus the efforts of many towards a measurable task.

Communities of practice are groups whose members regularly engage in sharing and learning driven by their strong shared professional identity. They are often organically created, with as many objectives as there are members in the community, existing as long as the members believe they can contribute or gain, and the membership is defined by the knowledge of the members. Communities of practice are a widely recognised way of capturing and exchanging tacit knowledge.

Studies have shown that workers spend a third of their time looking for information and are five times more likely to turn to a co-worker rather than an explicit source of information such as a book, manual or database
[Source: Davenport & Prusak, 2000].

An important aspect and function of communities of practice is improving organisational performance by shortening the learning curve of new employees, responding more rapidly to customer needs and enquiries, reducing rework and preventing ‘reinvention of the wheel’, and spawning new ideas for products and services
[Source: Lesser & Storck, 2001].

The Challenge arises when organisations face a recurring task of significant proportions, e.g. managing an important intangible asset like business data. This requires effective building and transfer of both explicit and tacit knowledge and innovative organisational forms.

Stuck between business and functions

Organisational challenge of knowledge-intensive professions

Professions like data management, change management and business analysis often do not have a clear organisational ‘home’. Leaving these tasks to grass-roots, communities of practice make management understandably nervous due to the consequent lack of control. In principle, these tasks can be entrusted to a function or a business unit, and they often are. But here comes the Challenge.

The organisational parentage of these tasks is ambiguous – they often fall in the cracks between business and one or several functions. Professionals doing these tasks are often dispersed geographically and therefore cannot be easily organised into teams. They often do not have a clear professional identity, and typically a small group of core professionals are supported by up to ten times as many ‘grey-zone’ employees who perform the task without defining it as such, which complicates learning and information exchange, especially across organisational units and boundaries.
[Source: project data]

The task often is continuous, and thus cannot be effectively addressed via a time-bound project team. And if the organisation is a complex global matrix with plenty of processes and operational level agreements (OLAs) already in place, adding yet another prescriptive process may look good on paper, but will not get the management the result it wants – the task managed appropriately.

Effective data management

One of the key Challenges that companies in asset-intensive industries presently face is how to effectively manage their business data as an asset, i.e. maximise the utilisation of their physical assets based on data, and reduce cost associated with gathering, maintaining and retiring of data. In industries like pharma or oil & gas, data management does not have a natural home, and sits in-between business and IT, and sometimes falls through the cracks.

Data management has a huge and an often underestimated impact on business, not least because it helps minimise risks and losses. It supports investment decisions that in pharma and oil & gas companies can add up to billions of dollars in annual spend. The risk of taking an ill-informed decision leading to a multi-billion investment, or one that Results in regulatory non-compliance or an accident is potentially catastrophic. Also, the database of information generated on the back of these huge investment decisions is also expensive to handle.

Industry data shows that without effective data management, up to 5% of data is lost and re-acquired annually and up to two thirds of time is spent searching and correcting inaccurate information.
[Source: client data]

Data management is a chunky task: in data-intensive business units, we estimate the
ideal required ratio is 1 Data Manager to every 10 Data Users [Source: client data]. The upside in improved finding and recovery of data is substantial. Similarly, the cost of data gathering, processing, maintenance and retirement can be handled more efficiently.

Turning data management into a well-managed asset is multi-dimensional and can be resolved only by adjusting the entire operating model of data management, including the explicit knowledge components (technology/tools, support services, portfolio of investments into data management capabilities), and the tacit knowledge component (data management processes, data governance, performance management, organisational capability and communications).

One important and often neglected tacit element of data management is organisational capability, i.e. role allocation, responsibility and accountability for data management decisions in business units and functions, as well as capability for creating, cross-unit sharing and learning of best practices in data management. 

We often find with our clients at the beginning of their organisational capability building journey that data management and similar professions often lack in clarity of organisational ownership, leadership and parentage. Their roles are defined loosely, with numerous business titles and job descriptions globally for people who essentially do the same tasks. That confuses and slows down knowledge exchange, learning and innovation, especially across geographies. Lack of a formal career path often leads to issues with attracting, retaining and developing of talent. 

In this loosely defined professional space, grass-root communities of practice have readily sprung up. They aim to facilitate learning and information exchange at least between core data managers who act as information accumulation hubs for the ‘grey-zone’ professionals and clients from other business units, functions and geographies. 

By their nature, they are unstructured initiatives and tend to rely on knowledge demand-supply forces within the broader data management community. But in a space so loose, awareness of and access to these communities is uneven, especially across geographies, and the result is rarely predictable.

The level of organisational support for these communities of practice varies. Management often feels uneasy about accepting communities of practice as a permanent solution to a task with potentially devastating consequences in the event of mismanagement. On the other hand, a dedicated functional team is often seen as a step too far: it implies artificial separation of data managers from the business they are meant to serve in an environment that may be viewed as already too siloed, structured and prescriptive.

Professional discipline in data management

A way to combine the best of functional teams and communities of practice

A new way of combining the community of practice and functional approach has recently emerged in asset-intensive industries. It's an idea that combines the best of two worlds: the enhanced social learning environment of communities of practice and the task orientation of functional teams. The name for it was coined by our clients - a professional discipline. The idea is simple: since imposing a new prescriptive process behind the task is expected to be counter-productive and disengaging, why not help data managers obtain something that in the past has measurably led to an enhanced learning and performance within communities of practice – a professional identity – and then actively steer it?

This example follows the steps of creating a professional discipline in data management:

  • Ensure clear leadership and organisational ownership of the new data management professional discipline – both in business and in the function, i.e. IT
  • Define organisational parentage for the data management professionals that spans business and function, and define the right mix of matrix reporting lines
  • Set out the global, regional and local responsibilities: we favour centralising processes and standards whilst decentralising delivery
  • Define essential professional roles within involved business units and functions and transition people into them
  • Build a performance management system around the new professional roles in order to achieve the improved data management targets
  • Identify the current and design the desired future organisational landscape in business and IT, and manage the transition with the associated training, recruitment, in/outsourcing and change management
  • Build professional identity and the community of practice across business and IT, by providing a genuine sense of recognition, professional community membership and career development paths for all professionals
  • Utilise the community of practice for learning, development, retention and attracting of talent by cultivating a DNA of experience, expertise, authority, energy and creativity.

Challenges of building professional disciplines

Over the time we have helped our clients in building professional disciplines, we have faced and overcome multiple Challenges.

The key Challenge is in how to marry a global model built around a unified set of standards and an important task with a decentralised organisation that is flexible enough to make local decisions, innovate and learn. Different business units and geographies operate at different levels of maturity, so it is a big task to define an organisational model flexible enough to fit all, but consistent and not adding to the cost.

Mapping the as-is capability of globally dispersed professionals and change-managing them through the reorganisation and the set-up stage of a community of practice is a laborious task. For a core population of 300-400 we are looking at a six months to a year-long transformation programme, depending on the initial state of organisational readiness.

Furthermore, having delineated a profession, the next Challenge is how to turn it into a professional identity and how to build a community of practice around it that would successfully support learning and innovation across business units, functions and geographies.

There are more Challenges still:

  • How to organise for effective asset management and learning/information exchange?
  • How to make sure that the organisation does not stifle the community of practice behind it?
  • How to performance manage towards asset optimisation in an environment that's not fully a business or functional unit, but a set of rules and agreements between professionals and with their managers?

The scope of this article does not allow for addressing all these questions. For now, we shall only say that professional disciplines have been designed for and are successfully run by our clients. We'll elaborate further on the Challenges of building a professional discipline in the next articles of this Organisational Effectiveness series.

About the Human Capital Network

The Human Capital Network was established by the London Business School Alumni Human Capital Club as a discussion forum that promotes open debate on the cutting-edge issues in strategic organisational change and talent management.

We publish the cutting-edge research on organisational development and change, provide an online discussion platform on our blog http://humancapitalnetwork.blogspot.com and run the Organisational Development Speaker Series at London Business School.

Our distinguished speakers provide perspectives from industry, management consultancy, academia, and trade bodies. Through the presentation of best practice case studies, new research and group discussion, our three interactive panels will help you identify and tackle the key Challenges of organizational change. 

The past events of the Organisational Development Speaker Series covered such topics as employee engagement strategies for the downturn and beyond and building change-ready organisational cultures. The next event of the series will be held in October 2010.

The Human Capital Network’s events are designed for senior OD and change practitioners and attract LBS alumni and external guests alike. Attendees of our past events represent a varied mix of industries and organisations, ranging from small entrepreneurial innovators to FTSE 250 blue chips, greatly contributing to the quality of panel interaction and the after-panel networking.

About Maja Stone

Maja is a principal with Molten Group in London. Maja advises her clients on change management, organisational design, business process reengineering, and technology transformation. Maja’s diverse experience spans a range of line management and consulting roles in blue-chip organisations ranging from Deutsche Bank to Vodafone, Thomas Cook, BP, and the Home Office, in Japan, the UK, Finland, and Canada. Maja holds an MBA from London Business School.