Presenting large scale forecast results in an intuitive way An industry case study. David Edison

Moore Stephens Consulting Limited Part of Moore Stephens LLP: –Founded in London in 1907 –Specialist expertise in Business Intelligence and forecasting –19,300 staff in 621 locations in 95 countries –Global turnover last year $1,844M –Part of Moore Stephens International, offering accounting and consulting services to all industries in all locations –Microsoft Gold Partner –Ten years of modelling

General Forecasting Issues Presenting statistics to people who don’t understand statistics Providing all projection results, rather than just the selected few Single-use datasets and models

Project Overview Major tobacco manufacturer Projection of manufacturer and competitor sales Automated, low level forecasting system Facility for ad hoc forecasting Integration with existing IT systems NOT a ‘black box’

Forecast Requirements Forecasts to be made monthly, automatically For next 60 days, 24 months, 5 years For each of 50+ geographical regions For each of 300+ tobacco products i.e. over 1 Million variables forecast each month Generic model, indicating confidence in results

User Interaction NOT a ‘black box’ – models to be built in Excel Users to be able to see and influence models Ability to add subjective assumptions and influence results Users to be able to experiment (ad hoc is optimal solution

Data Sourcing Objective forecasts driven by past data Automatically sourced from existing systems (cubes) Explanatory variables investigated included: –Various economic data –Tourism –Price: absolute and relative to market average –Various time data / day of the week / month of the year –Days until next / since previous trading day –Promotions, marketing campaign data

Specific modelling functionality Allow users to enter explanatory variable assumptions Allow selected historic data to be ignored Make anticipated proportional adjustments Enter expected ultimate results Apply subjective weightings throughout, effectively allowing for anywhere from fully objective to fully subjective forecasting All at the very lowest level Switching of variables

Proof of Forecasting Concept Generic forecasting required to be more accurate than existing, manual forecasts Model proven using multiple regression analysis (StatTools) Blind forecasts retrospectively made on 100 key datasets: an average of half the error term of previous projections = project approval Agreed was best and only tool for forecasts All controlled by and StatTools VBA

Presentation of Results Did not just want a lever arch file or series of Excel spreadsheets Specific high level key exhibits required (Excel) Flexible, freestyle analysis required, both of past and forecast data (Business Intelligence) What IS Business Intelligence?

What is Business Intelligence? “The ability to easily report, analyse, interrogate and manipulate any aspect of your business performance, when you want, how you want, where you want, irrespective of underlying systems technology” After Business Intelligence Data presented in your BI system Before Business Intelligence Data In Your Existing Systems

Sourcing of Data / Return of Results Business Intelligence Cubes (automated direct querying) ProClarity (briefing books)

Business Intelligence: Additional Functionality Fully web deployable Integrates fully with IT environment Not an IT tool – it’s for business performance, from analysts to executives Fits any business model One version of the truth Provides the speed and agility to make the difference

What could we have done differently and why did it work? & StatTools – a powerful, flexible combination Users have complete control over assumptions and understand the models Users are able to experiment with the ad hoc model, meaning they understand the impact their assumptions will have on the automated system

Questions? David Edison +44 (0)