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TRANSCRIPT
Adding Predictive Modelingto your Forecasting Process
Presented by:
Alex Ladd, CEO MindStream Analytics
Award-Winning MindStream Analytics
Local presence. Global reach.
• Advanced Analytics Practice
• Financial Transformation
• Expertise across all verticals
• Credentialed Compass Project
Management Methodology
• Headquarters: Boston, MA
• Consultants: US based
• Average Client size - $5B
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Alliance – 24x7 Coverage
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• Specialized | Certified Staff
• 30+ Global Managed Services
team members
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solutions
Outline
• Presentation Goals• Lots of Misconceptions out there about Predictive Analytics
• What cannot be done in order to leverage predictive analytics in forecasting
• How to start putting predictive analytics into your forecasting process
• What Predictive Analytics is NOT
• What Predictive Analytics is
• The misconceived idea of how to add it to a forecasting process
• How you really need to put it into you forecasting process
ANALYTIC-DRIVEN ORGANIZATIONS are distinguished by their ability to leverage …
All perspectivesPast (historical, aggregated)
Present (real-time)
Future (predictive)
All decisionsMajor and minor
Strategic and tactical
Routine and exceptions
Manual and automated
All informationSurveys
Social data
Enterprise content
All peopleAll departments
Experts and non-experts
Administrators and instructors
Agenda
• Misconceptions about Predictive Analytics• What it’s not
• How it’s thought to be put into forecasting
• What Predictive Modelling is
• How can we add it to the forecasting process?
What Predictive Analytics Is NOT!
• A magical process where you enter a few variables and Viola you have a forecast
• The correct way to do things for every piece of your forecast
• Something that makes humans irrelevant
Not Magic…
Predictive Forecasting?
Predict the entire Income Statement at once− Get lots of years of the Income Statement and run it through a
Monte Carlo model to create next year’s Income Statement
What is Predictive Analytics?
Better predict customer behavior, increasing profits and revenue
• Empirically-derived models used for predicting future outcomes
What Predictive Analytics Is
• Tool to illustrate the most probable outcome based on available data
• A tool to validate a human forecasting model
• Models also show which data factor is most influencing the probability
Goals of Predictive Analytics
• Bring key business insights into our decision-making processes
• Solution to our biggest challenges with data mining
• Integration of predictive analytics with data driven decision making
• Positive ROI and superior outcomes
Predictive Analytics helps connect data to effective action by drawing reliable conclusions about current conditions andfuture events
AlignAlign your organization
around information
Manage, integrate and govern
both traditional and big data
information sources to create a
foundation for analytics
Anticipate See, predict, and shape
business outcomes
• Understand, at all times, what is
happening & why
• Look forward to model & predict
what could be happening
ActAct with confidence at point of impact
• Embed analytics into key
organizational processes
• Empower a culture of data-
driven decision making
Transform
Learn
How can Predictive Modeling be used in a forecasting process?
How to get startedIdentify place to start
• What can you model? • Identify pieces of your financial forecast that you can build models for• Build a plan of what models first, second, etc.
What you’ll need• Rich data set, the richer and more complete the
better− Enrich your own data with external data
• Modelling tool− Microsoft Machine Learning Studio− IBM SPSS− R− RapidMiner− SASExecute
• Define achievable goals • Build on small wins to launch larger initiatives
How to build Predictive ModelsCRISP-DM
6 Phases1. Business Understanding
2. Data Understanding
3. Data Preparation
4. Modeling
5. Evaluation
6. Deployment• Not strictly ordered
• Several possible entry points into the loop
• Reflects iterative nature of data mining
Short Example – Office Supplies
Forecast Office Supplies• Take a look at past spend and transactional data for past spend
• Enrich that data with projections of general office supplies for next year from government or economic sources
• Create model to estimate costs next year
• Add the prediction to the Forecast P&L
How Companies are using it Today
• Build forecasts with predictive models that are compared against human built forecasts
• Have lots of models for individual predictions of small portions of their financial plan
• Have lots of rich data they can mine
• Understand master data
Data Enrichment Resources• National Bureau of Economic Research
• http://www.nber.org/
• US Government• https://www.data.gov/
• Data Science Central• https://www.datasciencecentral.com/
• https://www.datasciencecentral.com/profiles/blogs/top-20-open-data-sources
• American FactFinder• https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
• US Bureau of Labor Statistics• https://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=1#reqid=70&step=1&i
suri=1
