Explore the kind of expertise we are able to deploy.
(Tools courtesy of Blackshore Business Solutions)
Our Services: TRAINING - CONSULTANCY
'Inaccurate forecasting' is one of the most common management gripes. Attempts to deal with it have been thwarted by our inability to measure forecasting performance and do something about it in good time. This is how our tools - f(assist) - tackle the issues managers face when trying to improve the reliability of forecasts:
Q: How well can you measure forecast accuracy?
A: f(assist) helps distinguish between unavoidable unsystematic error (random variation) and avoidable systematic error (bias) - the root cause of unreliable forecasts
Q: Do you know the 'margin for error' attached to your forecasts?
A: Error is inevitable. f(assist) helps identify the size of the error associated with factors such as market volatility and the size of the business. It is futile to try to explain or eliminate variation within this 'margin of error'.
Q: In analysing forecast outcomes how well can you distinguish significant signals from background noise?
A: f(assist) strips out 'noise' (random variation) to isolate bias 'signals' - these either tell us that the quality of your forecasting process is suspect or that the business environment is changing. In either case you need to change your forecast process if it is to remain reliable.
Q: How quickly can you detect change in forecast quality or business drivers?
A: Spotting a problem at the end of a year is likely to be too late. f(assist) works in real time: one additional piece of data is enough to allow it to detect a deterioration in forecast quality.
Q: Do you have a forecast improvement methodology?
A: The only way to improve is to learn. If you can't spot failure you can't learn. f(assist) spots evidence of failure in real time, helps trace the cause of failure and thus remedy it.
Q: How well can you measure forecast accuracy?
A: f(assist) helps distinguish between unavoidable unsystematic error (random variation) and avoidable systematic error (bias) - the root cause of unreliable forecasts
Q: Do you know the 'margin for error' attached to your forecasts?
A: Error is inevitable. f(assist) helps identify the size of the error associated with factors such as market volatility and the size of the business. It is futile to try to explain or eliminate variation within this 'margin of error'.
Q: In analysing forecast outcomes how well can you distinguish significant signals from background noise?
A: f(assist) strips out 'noise' (random variation) to isolate bias 'signals' - these either tell us that the quality of your forecasting process is suspect or that the business environment is changing. In either case you need to change your forecast process if it is to remain reliable.
Q: How quickly can you detect change in forecast quality or business drivers?
A: Spotting a problem at the end of a year is likely to be too late. f(assist) works in real time: one additional piece of data is enough to allow it to detect a deterioration in forecast quality.
Q: Do you have a forecast improvement methodology?
A: The only way to improve is to learn. If you can't spot failure you can't learn. f(assist) spots evidence of failure in real time, helps trace the cause of failure and thus remedy it.
We all know that 'single point' plans and forecasts are misleading because they take no account of risk - the certainty that things will turn out different to expectations, either because of underlying volatility or the impact of significant events that cannot be estimated with certainty. Understanding risk enables managers to build better plans; with a known risk profile, and contingency plans to mitigate risks and exploit opportunities.
Q: How much risk is attached to your plans and forecasts?
A: The only thing we can be sure about with conventional 'single point' forecasting is that they will be wrong; f(risk) helps you to understand by how much and in what way they might be 'wrong' and so improve the quality of decision making.
Q: What is driving the risk profile?
A: f(risk) helps identify what is driving the risk profile of your business: the inherent risk of operating in a particular market in a specific way (based on historical record), and risk associated with new events (using estimates based on business judgement).
Q: What can you do to mitigate the risk or exploit any opportunities?
A: f(risk) helps you to understand what is driving the risk profile and so put in place contingency plans. Naive attempts to add up risks arithmetically will lead to exaggerated estimates and consequently potential management overreaction. f(risk) has clever tools 'under the bonnet' which allows user to combine risks statistically without expert help
Q: How do you measure the quality of your Range Forecasts?
A: f(risk) has tools to scientifically measure The quality of a range forecast based on 'hits' and allowing for sample size.
Q: How much risk is attached to your plans and forecasts?
A: The only thing we can be sure about with conventional 'single point' forecasting is that they will be wrong; f(risk) helps you to understand by how much and in what way they might be 'wrong' and so improve the quality of decision making.
Q: What is driving the risk profile?
A: f(risk) helps identify what is driving the risk profile of your business: the inherent risk of operating in a particular market in a specific way (based on historical record), and risk associated with new events (using estimates based on business judgement).
Q: What can you do to mitigate the risk or exploit any opportunities?
A: f(risk) helps you to understand what is driving the risk profile and so put in place contingency plans. Naive attempts to add up risks arithmetically will lead to exaggerated estimates and consequently potential management overreaction. f(risk) has clever tools 'under the bonnet' which allows user to combine risks statistically without expert help
Q: How do you measure the quality of your Range Forecasts?
A: f(risk) has tools to scientifically measure The quality of a range forecast based on 'hits' and allowing for sample size.
* How credible is this forecast/plan in the light of past performance?
* What is the source of my problem with forecasts?
* How can I set stretching but 'fair' targets?
* Are my results significantly different from targets?
* Are my recent results significantly different from trends - short, medium and long term?
* What stock should I be holding? Where do I significantly hold too much or too little stock?
Please contact us if you want to find out more about what we can do to help you.
* What is the source of my problem with forecasts?
* How can I set stretching but 'fair' targets?
* Are my results significantly different from targets?
* Are my recent results significantly different from trends - short, medium and long term?
* What stock should I be holding? Where do I significantly hold too much or too little stock?
Please contact us if you want to find out more about what we can do to help you.