Interview: Andrew Duguay, Prevedere on Economic Intelligence from Integrating Public Datasets
We discuss Analytics at Prevedere Software, understanding the impact of external factors on a company’s performance, features of in-memory correlation engine and economic intelligence by Prevedere.
Twitter Handle: @hey_anmol
Andrew Duguay is a Senior Economist & Data Scientist with Prevedere Software. Prevedere is a Big Data Predictive Analytics solution that helps companies increase profits and outperform competition by automating the analysis and identification of leading external drivers that improve forecast accuracy.
Andrew graduated from Gordon College with a degree in Economics. He has received a Certificate in Professional Forecasting from the Institute for Business Forecasting and Certificates in Economic Measurement, Applied Econometrics, and Time-Series Analysis and Forecasting from the National Association for Business Economics. He is also co-owner of a small business in central New Hampshire where he resides.
Here is my interview with him:
Anmol Rajpurohit: Q1. What does Prevedere Software do? What role does Analytics play at Prevedere?
Andrew Duguay:
Prevedere is a cloud based application for improving company decision making by finding leading external drivers and building highly predictive models of internal company data based off those drivers.
Prevedere leverages the capabilities of the cloud to enable business analysts to perform correlation analysis and advanced analytics on over 1.5 million external time series data sets in a matter of minutes.
AR: Q2. What are the major external factors that have a significant impact on a company's performance?
AD: A recent Harvard Business Review study found that over 85% of your company’s
performance is due to external factors. Everything from disposable income, inflation, exchange rates, interest rates, and even non-economic factors like the weather are significantly influencing business trends over time. Each company is different, and that is why it is important to have a system for finding the leading drivers that impact your specific business the most.
AR: Q3. What are the unique features of Prevedere In-Memory Correlation & Pattern Matching Engine?
AD: A few years ago, this type of massive data crunching was not even reasonably possible, but thanks to advances in cloud computing and in-memory processing, Prevedere is able to spin up servers to run correlation analysis between your company variables and our large repository of data sets to find correlation, lead time and other measures in a matter of minutes.
The sheer volume of analysis would have taken a detrimentally long time to do with traditional tools such as Excel or legacy statistical packages, making this a new and unique way of harnessing and finding analytical value in Big Data. Our patent pending software uniquely provides any company a competitive advantage.
AR: Q4. Prevedere has over 1.5 million external data sets in its systems which it uses to correlate with client data in order to generate insights. What are some examples of these external data sets used by Prevedere?
AD: Prevedere gathers data from many familiar sources such as the Census Bureau,
Bureau of Economic Analysis, Institute for Supply Management, the World Bank, and many more widely accepted sources of economic data. Prevedere is a gathering place for publicly available data that is structured, time series, and could possibly relate to businesses.
Businesses are using Prevedere to see how their internal metrics are relating to common economic indicators such as Gross Domestic Product, Housing Starts, Consumer Sentiment, Disposable Personal Income and the Purchasing Managers Index.
AR: Q5. What are the key capabilities of Economic Intelligence software by Prevedere?
AD: The main features of Prevedere Economic Intelligence include the following:
AR: Q6. What are your favorite client use cases? What features do clients appreciate the most?
AD: A global leading manufacturer was in need of identifying leading external market drivers to increase profitability and decrease costs. We looked at five years of historical
sales, volume and costs across 3 business lines, 3 countries and 27 product types by state. We analyzed their internal data against over one million external data sets looking at both economic and weather related factors.
Prevedere helped this company build 158 predictive models in just six weeks. The company said that the Prevedere forecast models helped “strip the bias out of the forecasting process” by looking at the external drivers and the result was an increased monthly forecast accuracy from 77% to 98%. The improved forecasting helped the company achieve 26% year over year increase in monthly revenue and eventually a successful filing for an IPO.
Second part of the interview
Anmol Rajpurohit is a software development intern at Salesforce. He is a former MDP Fellow and a graduate mentor for IoT-SURF at UCI-Calit2. He has presented his research work at various conferences including IEEE Big Data 2013. He is currently a graduate student (MS, Computer Science) at UC, Irvine.
Related:
Andrew Duguay is a Senior Economist & Data Scientist with Prevedere Software. Prevedere is a Big Data Predictive Analytics solution that helps companies increase profits and outperform competition by automating the analysis and identification of leading external drivers that improve forecast accuracy.
Andrew graduated from Gordon College with a degree in Economics. He has received a Certificate in Professional Forecasting from the Institute for Business Forecasting and Certificates in Economic Measurement, Applied Econometrics, and Time-Series Analysis and Forecasting from the National Association for Business Economics. He is also co-owner of a small business in central New Hampshire where he resides.
Here is my interview with him:
Anmol Rajpurohit: Q1. What does Prevedere Software do? What role does Analytics play at Prevedere?
Andrew Duguay:
Prevedere is a cloud based application for improving company decision making by finding leading external drivers and building highly predictive models of internal company data based off those drivers.
Prevedere leverages the capabilities of the cloud to enable business analysts to perform correlation analysis and advanced analytics on over 1.5 million external time series data sets in a matter of minutes.
AR: Q2. What are the major external factors that have a significant impact on a company's performance?
AD: A recent Harvard Business Review study found that over 85% of your company’s
performance is due to external factors. Everything from disposable income, inflation, exchange rates, interest rates, and even non-economic factors like the weather are significantly influencing business trends over time. Each company is different, and that is why it is important to have a system for finding the leading drivers that impact your specific business the most.
AR: Q3. What are the unique features of Prevedere In-Memory Correlation & Pattern Matching Engine?
AD: A few years ago, this type of massive data crunching was not even reasonably possible, but thanks to advances in cloud computing and in-memory processing, Prevedere is able to spin up servers to run correlation analysis between your company variables and our large repository of data sets to find correlation, lead time and other measures in a matter of minutes.
The sheer volume of analysis would have taken a detrimentally long time to do with traditional tools such as Excel or legacy statistical packages, making this a new and unique way of harnessing and finding analytical value in Big Data. Our patent pending software uniquely provides any company a competitive advantage.
AR: Q4. Prevedere has over 1.5 million external data sets in its systems which it uses to correlate with client data in order to generate insights. What are some examples of these external data sets used by Prevedere?
AD: Prevedere gathers data from many familiar sources such as the Census Bureau,
Bureau of Economic Analysis, Institute for Supply Management, the World Bank, and many more widely accepted sources of economic data. Prevedere is a gathering place for publicly available data that is structured, time series, and could possibly relate to businesses.
Businesses are using Prevedere to see how their internal metrics are relating to common economic indicators such as Gross Domestic Product, Housing Starts, Consumer Sentiment, Disposable Personal Income and the Purchasing Managers Index.
AR: Q5. What are the key capabilities of Economic Intelligence software by Prevedere?
AD: The main features of Prevedere Economic Intelligence include the following:
Housing global datasets in a clear and consistent fashion, updated on a daily basis
- A patent pending correlation engine that will compare the 1.5 million data sets to a business’s internal data and sort the results in a matter of minutes
- User friendly workbench and charting capabilities for finding relationships between data sets
- Proprietary model building platform for creating company forecasts based off the lead time and statistical relationship of the economic variables
- Reporting and data exporting features for easy integration into any existing forecasting and planning process and system.
Housing global datasets in a clear and consistent fashion, updated on a daily basis
AR: Q6. What are your favorite client use cases? What features do clients appreciate the most?
AD: A global leading manufacturer was in need of identifying leading external market drivers to increase profitability and decrease costs. We looked at five years of historical
sales, volume and costs across 3 business lines, 3 countries and 27 product types by state. We analyzed their internal data against over one million external data sets looking at both economic and weather related factors.
Prevedere helped this company build 158 predictive models in just six weeks. The company said that the Prevedere forecast models helped “strip the bias out of the forecasting process” by looking at the external drivers and the result was an increased monthly forecast accuracy from 77% to 98%. The improved forecasting helped the company achieve 26% year over year increase in monthly revenue and eventually a successful filing for an IPO.
Second part of the interview
Anmol Rajpurohit is a software development intern at Salesforce. He is a former MDP Fellow and a graduate mentor for IoT-SURF at UCI-Calit2. He has presented his research work at various conferences including IEEE Big Data 2013. He is currently a graduate student (MS, Computer Science) at UC, Irvine.
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