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Hello and welcome, this is Gary Simon, Chief Executive of FSN and leader of the Modern Finance Forum on LinkedIn. 

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Today I'm very excited to present the findings of FSN's future of planning, budgeting and forecasting survey 2017, which builds on the success of our

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2016 research. At this point I'd like to thank our sponsor CCH Tagetik for their kind support in making this research

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possible. The research was crowed sourced from the FSN Modern Finance Forum on LinkedIn. 

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Nobody was incentified to participate in the research and with around 850 responses from senior Finance professionals it represents one of the largest

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and most authoritative surveys of CFO opinion about the BP&F process.

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55% of the responses came from Europe, 15% from North America, approximately 15% from Asia PAC 

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and then the rest scattered across the world. What we identified is that no matter where finance professionals are situated, they all face similar

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challenges. Almost half of the sample came from companies with more then a thousand employees and 25% from 

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organizations with more than 10.000 employees. This year's research shows a modest improvement 

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in the speed with which people can re-forecast, the accuracy and to some extent the distance over which they can look out on the time horizon,

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but we still find ourselves in the situation where only 50% of organizations are able to forecast with any accuracy

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beyond 6 months, only 41% are able to re-forecast the Enterprise in under a week,

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only 42% of organizations are able to re-forecast revenue within plus or minus 5%,

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and only 40% of organizations say their forecasting process is insightful.

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So we're not exactly covering ourselves in glory when it comes to planning, budgeting and forecasting, so what's going wrong?

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In this webinar I want to go through 3 areas: what are the factors that drive forecast accuracy and insight,

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what makes some organizations insightful and others not at all insightful,

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and what is the role of technology, especially experimental type technologies such as AI and machine learning 

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in improving the performance of planning, budgeting and forecasting; and we tend to look at 

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performance in 3 areas, first of all the speed with which we can re-forecast, secondly 

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the accuracy with which we can re-forecast and finally the distance out to the time horizon, how far out

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into the future can an organization forecast its results with reasonable accuracy.