This blog builds on our previous discussion on the EU Settlement Scheme. It highlights action managers need to take to enable staff to make short-duration visits to EU countries for academic, sales or technical activities. We point out that business trips will need to be planned in the future. It won't just be a case of booking a flight and putting equipment in a suitcase.
We hear bad things about the NHS. We are led to believe that all staff are stressed to blazes and unable to function properly in a broken system. But far from it. My conclusions from my brief period as voyeur are that these guys know how to make a system work. I think industry can learn a lot from the way that hospital staff interact. Here's the story that illustrates how.
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There are three centres of interest. Firstly, managers want to control anything that heightens costs. Secondly, managers are interested in anything that affects productivity such as competence, behaviour and the exploitation of technology. Thirdly, managers focus on variables that reduce competitive advantage through low staff motivation. This covers variables like commitment, engagement and leadership. But reports produced must provide insight. Here's how.
Many espouse the need for improved productivity but few have a formula for how to achieve it. In a Guardian article, the New Economic Foundation argues that if consumers have more money in their pockets, they will spend it. Spending is encouraged by giving employees more annual holidays. Firms will spend the resulting increased profits by investing in productivity. So, increased spending by reducing taxes, increasing minimum wage and giving more holidays will cause increased productivity. But will it work?
When it comes to HR data, there is a wealth of it to be collected and analysed. Indeed, the saying “if you can’t measure it, you can’t manage it” arguably holds true - how can you decide what to do to improve absence levels, and therefore sickness-related costs, for example, if you have no clue what those absence levels are? And yet, just because you can measure it, does not mean you should. This blog (the first of two) sets out what data you might gather and how you might interpret what you do.