Our management is obsessed about continuous improvement. Checking whether we’re (still) doing the right thing is extremely important. Are our learners enjoying their course? How is our customer service performing? How is our tutor support? How can we shave 1 step off a 10-step on-boarding process? What should we change to make things better? How do continue to further raise the bar? Etc.
It’s important to focus your efforts as you can only do so much. To help prioritise and make solid decisions you need to rely on business intelligence more often than your gut. This intelligence comes from distilled data but many companies just don’t get it. Too many firms waste precious time and resources to end up with huge databases with meaningless data, creating information based on too many assumptions and they ultimately suffer from flawed decision-making.
It’s actually not that difficult and here are some tips how you can avoid falling in the same trap.
Respect the time it takes to capture data
Put yourself in the following scenario. Imagine you’re providing a service to someone for the duration of 6 months – it can be anything that comes to mind. You think you need to know everything about that person to do the best possible job, but THINK AGAIN. Every moment that this person answers another question is valuable time. Are you sure they will get this back? Respect someone else’s time. Skip the nice to know information and ask yourself at least 10 times whether that piece of data is crucial or not. You’re forgiven if you think that this won’t apply in an automated environment, but even processing power needs to be respected (read on). Especially when you eventually want to re-cut that data into insightful analyses that support better decision-making.
More data leads to more costs
Total cost of ownership of data can get out of hand very quickly. More data means faster network requirements, more processing power, more storage space, more backup space, more expertise to mine the right data, bigger and longer “data projects” and it actually becomes far more confusing over the long run too. Familiar with these? “What is this bit of data again?”, “Why did we store that?” or “Who uses it?”. Ensure you consider the cost that data brings with it up-front. That’ll guarantee to make you think twice whether you REALLY need it or not. So remember this: total cost of ownership.
Old data is useless
Here I use the often-dreaded appraisal as my example. If you’re one of the lucky few who works in an environment where feedback is always timely, luck surrounds you. But most appraisals result in frantic last-minute gathering of feedback to create a ‘360 degree view’ that covers the past 6 or 12 months. Did this EVER result in any useful insights? Or when a project finishes and you’re asked to write a huge piece of paper containing 500 questions, most of them unimportant but seen to ‘tick the box’ so nobody can fault the firm later (yes, I said it).
This is where technology can help simplify things. In companies with lots of staff or members, a one-click “thumbs up” or down multiplied times 10,000 can be incredibly insightful. So why not implement that in company email?
Or another example, something we’ve implemented recently ourselves, a two-second 5-star rating once a learner finishes a lesson or module. They’re still “in the moment” which is the best time to ask, but you’ve got to keep it short and sweet; respect their time. And if you realise that it doesn’t necessarily lead to enhanced continuous improvement, you’ve tried – but now stop gathering it!
Of course there’s much more to it, such as the time it takes to actually extract meaningful business intelligence from the data you’ve captured, but these tips should get you off to a very strong start.
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The Health Sciences Academy Team
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