Your Revenue Driver
2021 Be The Expert
What comes first quality or profitability(i.e. not losing money?) We would like both at the same time -and yet often - there is recognition that the investment to create quality may come first by design for some situations. How long can we wait to experience profitability?
How long can we sustain spending more than we have to spend?
Where might we see a similar "Catch 22" in the workplace? Are there conditions under which we do not allow people to be re-hired or transferred or given salary increases?
Do we inadvertently sustain poor performance?
What checks and balances would assure proper balance of outcomes and costs?
How do each of these functions assure their proper balance?
The approach described in this article starts with performance and applies training as a remedy - so it seems more efficient.
Might it also attach a stigma with "being in training?" How would we remedy this?
What privacy concerns relate to training? What conclusions might be drawn if you knew what training was being taken by your manager or their manager or a co-worker that you are having challenges working with. Might someone draw conclusions about you if they knew what training you were taking.
What benefits occur from making training rosters "public?"
There is a lot of talk about technology and a lot of talk about the consumer experience.
Is anyone listening? Do we only hear what we want to hear?
How do we define better? Is our definition biased towards bigger or has bigger earned the reputation - most of the time?
How do we avoid bigger being better just because they do a better job of telling us they are better?
2021 Be The Expert
What makes an expert an expert?
Once an expert how does one continue to be an expert?
What is the purpose of being an expert?
What is the relative importance of:
What is a learning model?
What are the most common learning models?
How do we know which model to apply?
What shifts or changes in learning models have you experienced? Why? What are the performance results?
When is it important to remove bias from data analysis?
Is it possible to remove bias from data analysis?
Do you want it to be possible?
What alternatives exist if it is not possible?