How to Quickly Leverage Big Data Analytics May 23, 2013

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How to Quickly Leverage Big Data Analytics May 23, 2013



• 3V’s of Big Data

• Value of External leading indicators • Buy vs. Build Dilemma

• Case Study - Dow Chemical Company

• Case Study - Advanced Drainage Systems • Methods to Identify Leading Indicators


What is Big Data

“Big data” is high-volume, -velocity and -variety information assets that demand cost-effective,


Clearly, knowledge is power

It’s why we know our internal data -- down to the decimal

Profit Margin EBITDA


But according to experts, external data

is even more important

Companies who consistently review industry indicators

outperform peers by 220%


85% of a company’s


Problems to solve

• Global economic changes impact company results

more frequently and with greater depth than ever before

• Companies scramble to find external data for

upcoming board or leadership presentations

• Companies have redundant sources and spend for

external data

• External data is not systematically analyzed against

internal results

 Forecast accuracy suffers lowering profits

 Results suffer due to staying in existing markets to long or entering new markets to late


It’s a lack of systems to consistently collect, verify and interpret information effectively

The problem is not a lack of data,

and it’s certainly not a lack of will


Big Data Projects

• Build in house expertise on existing tools • Build in house expertise on new tools


Case Study – DOW Presentation

• Overview

– Goal was to leverage external leading drivers to improve

forecast ability for several layers of business

• Within 5% very good

• Within 10% Good

• 10%-15% useable

• >20% needs work

– Decided to build with internal team, internal SAS and BI tools

and external consulting

– In 6 months they were able to forecast total net sales with


Case Study


– Goal was to leverage external leading drivers to

improve forecast ability at region and product level

• Within 5% very good

• Within 10% Good

• >10% needs work

– Decided to partner with one provider

– In 6 weeks they were able to forecast at product


Case Study – Global Manufacturer

Patented- automated leading indicator

126,000+ External Data Series

Economic Data Customers &

Competitors Demographics

$ales Volume EBIDTA


High Level Activities

Data Gathering and Structuring Leading Driver Identification Model Building and Tuning Implementation and Training • Internal Data • Business Attributes & Hierarchy • External Data Sources • Suppliers • Competitors • Customers Statistical Analysis • Regression • Lead/Lag • ProCyclic • CounterCyclic ROCET Methodology Engage business leaders Billing Days adjustments Variable Reduction Variable Selection • Cross Correlation • Co-integration • Similarity

and Back testing

• Finalize accounts and Permissions • Deploy workbench and models • Update Calendar • Set Alerts • Training and handover • Ongoing Support

8 Week Project


Data discovery Systematic Indicator analysis Interface for automation




Case Study – Highlights


– 3 Internal FTE

– 11,000 Data Series from one provider – 34 Models produced by experts in

economics and statistics

– Forecast down to state and product


– No internal hardware or IT system


Big Data - Build or Buy

Build Buy


• Own the IP of the

finished product

• Build deep technical

in house expertise

• Expertise of provider

• Can select best of breed


• Shorter time to implement

• Internal staff stay focused on

core business


• Long time to create

• High internal cost

• May still need experts

• Acquisition Cost


Identifying Leading Indicators

Key Steps

– Detective Work – Format Data

– Chart and Graph to

identify correlation

– Make it a repeatable


Thorough analysis

Proprietary algorithms parse data,

analyze influences

and forecast future financials

17+ patents pending

Certified in Time Series Analysis and Forecasting by NABE


Accurate and insightful outputs

Clear picture of business cycle Comprehensive outlook


Actionable insights

“Our CFO and finance organization has to do detailed analysis of economic indicators vs. our business results. The amount of time and effort is immense. Prevedére eliminates the manual part of this analysis and makes it repeatable. Further, our private equity owners are extremely interested in our performance vs. economic indicators. Using

Leading Indicator Analysis


Better predictions

Better actions

Better results

What would 94+% forecast accuracy mean to your bottom line?

Companies that build and verify

a set of leading indicators earn a

2.95% higher return on assets and a 5.14% higher return on equity.

Wharton 95 85 90 85% 94% forecast accuracy


Start conservatively

A paid trial can be completed in just 2-3 weeks See exactly what reports and insights

you would get for your specific company, indicators and priorities




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