A metallic "please come in" sign hangs against a glass wall reflecting lights.

Getting On-Boarding Right for a Healthier Organisation

By Sam Robinson

While talking to a client in a government organisation recently, I realised how sloppy I am when talking about onboarding and induction programs. For the sake of clarity (I love clarity!) a few definitions:

  • Recruitment: the broad process of attracting and selecting people to join an organisation
  • Selection: choosing a single candidate for a role (part of a selection process)
  • On-boarding: the process of integrating an individual into an organisation, whether this is based on skill development, cultural norms and beliefs, or systems and process knowledge
  • Induction: the process of informing a new employee about an organisation’s policies, systems and procedures (part of an on-boarding process)

I’m not an HR professional, despite LinkedIn assuming I am, so please excuse the lack of convention. These are definitions I find helpful and I’m not suggesting this is “the general consensus” or an “industry standard”. (By the way – a topic for another time – what do you think when people throw in those phrases?)

I want to focus on on-boarding because it’s often relegated to the “we strongly intend to look into this in the next financial year” pile. Looking at an on-boarding process can provide a window into the health of an organisation. When I’m helping an organisation improve, I look at an on-boarding process as evidence for:

Shelved, lopsided black binders

Managing Customer Data the Right Way: 10 Basic Principles

By Chally Kacelnik

Let’s consider how to manage customer data the right way: ethically, usefully, and achievably. With scandal after scandal about the misuse of customer data making headlines, it’s no longer possible to think of data as something neutral or passive that gets collected and sits out of sight and mind.

We’re seeing rapid changes to how we think about the collection and use of data. One major theme of the day is technological innovation. Traditional boundaries are being tested, with even governments feeling out how public and distributed innovations like blockchain could work for them. Another theme is dread. There’s a distinctly dystopian resurgence of anxiety about surveillance and poor or actively harmful data management, and unfortunately we’re seeing that suspicion justified. It’s vital for organisations – particularly government ones – to understand that data is fraught and to take a thoughtful approach to the ethics, reach, volume, and scale of the data they collect and use.

Within organisations, there tend to be two opposed approaches. There are those who trust in tech to solve data problems, the more innovation and more data collected the better, even if it’s not fully understood. Then there are those who trust their own workarounds more: the people who have their paper folder or their spreadsheet sitting on the side, whether because the system isn’t set up usefully, there isn’t an established way of working that encourages the right kind and quality of data isn’t being entered, or because of habit and comfort.

Increasingly, the uses and abuses of data are so top of mind and so poorly understood by most of us that organisations are tending to throw everything at the wall. It’s all too common for organisations to take the approach of investing big in new systems without understanding how to drive them effectively, ending up with messy data that causes lots of headaches, rework, haphazard ways of working across the organisation, and reinforcement of those two opposed approaches (including workarounds on top of workarounds!).

In short, if you throw everything at the wall, you’re going to find cracks. Technology isn’t a wilful force in and of itself (at least not yet!) and should be a facilitator rather than a driver. Positive, active human behaviour should drive how we interact with data and how we use technology to facilitate that interaction. Let’s get back to the very basics of what organisations need to do with data: serve their customers.

Here are seven principles for achieving that aim by managing customer data well at the ground level:

Lightbulbs hanging from ceiling

I’ll level with you: “Levels of Work” tips and traps

By Sam Robinson

A useful model that supports people to work well together in an organisation is the concept of “Levels of Work”. Familiar to many, it’s also one of the toughest things to grasp for people new to organisational theory (for an explanation, see the Systems Leadership: Creating Positive Organisations book).

Essentially, Levels of Work proposes that work differs in complexity in organisations and the predominance of a certain level of complexity determines the Level of Work. (When work tasks are grouped together, this is called a “role”.) By complexity, I’m talking about the range and degree of ambiguity in variables having an impact on decision-making.

If you’ve ever worked at different levels in a large organisation, there are plenty of examples you’ll be familiar with. The first entry-level job you had when you came into an organisation is likely to have had fewer variables and a shorter impact horizon for your decisions than your later, more senior roles. For example, someone working in a team on a construction site laying the foundations for a new building is performing different work to someone leading a construction crew and being concerned with things like materials being ordered on time, the well-being and productivity of individuals, and the whole project moving forward as it should.

Levels of Work, once understood for the first time, is a real light bulb moment. Helping to shine a light on the actual value that an individual role should add to an organisation often entails reflection that opens a whole new world of understanding about work. For me, it helped me to understand my frustration with managers I’ve had in the past who dipped down and tried to work at “my” level.

But be careful.