Business Case: Sales forecasting with SAS Advanced Analytics for the Pharmaceutical sector.
Post on 15-Jul-2015
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Sales forecasting with SAS Advanced Analyticsfor the Pharmaceutical sector.
A business case
Blue BI is a growing company that provides IT consulting in the Business Intelligence &Analytics environment.
Our mission is turn data into actionable insights: we help organisations to take fasterand smarter decisions and tackle the most complex business issues.
Blue BI offers a comprehensive set of Business Intelligence end to end services, fromPOC’s to Application Management, in the following areas:
Corporate Performance ManagementBusiness Intelligence & AnalyticsData Warehousing
Our organisation our organization is formed by a group of professionals with morethan ten years of experience, located in our offices of Milan, Turin and Rome.
Blue BI: Company Profile
Blue BI S.r.l.2
Blue BI’s deep business and technology experience combined with the wide range ofSAS applications, delivers to the market a competitive offer based on the followingelements:
Extensive expertise in some industries (i.e. Life Sciences) and delivery capabilities
Functional and technological competences on SAS® software solutions
Flexible and scalable approach based on tangible and proven results
Usage of predefined data model as project accelerator: BBI x Pharma
Option for Cloud and SaaS (Software as a Service ) system deployment
Blue BI: SAS Partnership
Blue BI S.r.l.3
Blue BI plans and builds Business Intelligence & Analytics systems in several industries , with a specific focus inLife Sciences, where we can include among our customers some of the most important domestic and foreignorganisations .
Our specialisation is based on the following distinguishing elements:
extensive and long lasting experience on the specific business processes and analytics needs
Effective implementations of reporting& analytics systems in several areas, such as:• Sales Forecasting• Sales Analysis (Internal/External)• Geo Marketing Integration and market research• Social media analysis• CRM Analytics Sales Force / Field Force Effectiveness• Planning & Control• Logistics analytics
Mobile applications
Cloud & Software as A Service deployment
Blue BI and the Life Sciences industry: BBI x Pharma
BBI x PHARMA
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Is a combined analysis of qualitative and quantitative componentsaimed to predict the sales performance, in the short, medium and long period.
Quantitative components: time series that provide evidences of pastperformance
Qualitative components: known or presumed elements whichare not represented by the time series
What is Sales Forecast ?
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To rely on the most possible accurate and reliable Forecast Model for sales allows you:- in the short period, to organize business functions and resources- in the long period, to plan investment programs- in general, to support strategic decisions
In a global and high competitive scenario, where markets are rapidly and constantly changing, forecast analysis is usefull especially in the short period. (6-12 months)
Why is Sales Forecast becoming increasingly important ?
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Business Case
Company: One of the world’s largest biotech companies, with more than 7,000 employees across six continents and a rapidly expanding product portfolio and a growing pipeline.
Business Area: The company provides medical product support across the Hospital Channel
Business Needs: Understanding the adoption of the existing products and predict adoption of new products allows to increase the customer service, adoption and eventually profitability
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Project Phases – Step 1
Visualize and Analyze the
Model
Apply Regression Algorithms
Collect and Analyze
HistoricalData Series
Collected 24 months «Internal» Sales data by Product / Territory / Region
Loading Dataset in SAS Forecast Server
Forecast Model Review
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Project Phases – Step 1
Visualize and Analyze the
Model
Apply Regression Algorithms
Collect and Analyze
HistoricalData Series
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Project Phases – Step 2
Stock Estimate using IMS Sales compared to «Internal» Sales
Daily Average Consumption evaluation
Stock optimization index calculation
Load the Stock optimization index in SAS Forecast Server as a regressor
Visualize and Analyze the
Model
Collect and Analyze
HistoricalData Series
Apply Regression Algorithms
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Stock Estimate using IMS Sales compared to «Internal» Sales
Daily Average Consumption evaluation
Stock optimization index calculation
Load the Stock optimization index in SAS Forecast Server as a regressor
Project Phases – Step 2
Before regression….
...after regression
Visualize and Analyze the
Model
Collect and Analyze
HistoricalData Series
Apply Regression Algorithms
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Project Phases – Step 3
Visualize and Analyze the
Model
Apply Regression Algorithms
Collect and Analyze
HistoricalData Series
Import Predictive Model in SAS Visual Analytics
Visualize and Analyze the results
Analyze the model generates new questions
Refine the Predictive Model with new regressions
Validate the analysis and decision support
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Project Phases – Step 3
Visualize and Analyze the
Model
Apply Regression Algorithms
Collect and Analyze
HistoricalData Series
From analysis to delivery in 1 month
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Predict Adoption for new products
The issue:- Lack of an appropriate time series ( <24 months)
Solution:- Time series of a product with equivalent sales characteristics- Implementation of a configurable growth curve
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Technical Architecture
27/7 server availability
SAS licenses deployed in SaaS mode
Support services included in the periodic fees
End to end Blue BI support: Project implementation, Application and System management
Business Continuity: high availability, fault Tolerance, Disaster Recovery, …
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Benefits Strong improvement of the Sales Forecast accuracy
Quick R.O.I in terms of enhanced effectiveness in the sales and distribution processes
Reaction time increase: better time-to-market
More compliance with corporate requirements
Users empowerment, better understanding of the business processes
Full automated forecasting process, previously costly and totally hand made (Excel), with:o Automatic selection of the best statistical modelo Manual override opportunity to manage not predictable qualitative elements from the statistical model
(i.e. new competitor product launch)
Low cost and flexible technical infrastructure with no impact on the corporate governance guidelines Blue BI S.r.l.
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Q & A
Please contact us at marketing@bluebi.it
Milano
Via Caldera, 21Palazzo C320153 Milano
Tel. +39 02 40916905
Torino
Corso Filippo Turati, 1010128 Torino
Tel. +39 011 19909494
Roma
Via Giambattista Vico, 3100196 Roma
Tel. +39 06 32101400
Blue BI S.r.l.
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