Copyright © 2014 Oracle and/or its affiliates. All rights reserved. BI Cloud Service Sales Pipeline App V410
Copyright © 2014 Oracle and/or its affiliates. All rights reserved.
BI Cloud Service Sales Pipeline App V410
Copyright © 2014 Oracle and/or its affiliates. All rights reserved.
What is it ?
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• Oracle BICS QuickAnalytics Apps provide rapid deployment applications that deliver powerful turnkey BI
on top of BICS data-sources. Best practice Business model, Reports and Dashboards are prebuilt within
QuickAnalytics Apps and immediately deliver powerful Business intelligence.
• The Pipeline App offers pre-built analytics on Sales Opportunities which are at various stages in a Sale
Pipeline. In addition to pre-built BICS data model, seed data, reports and dashboards, this app is also
packaged with a simple APEX transactional application for working with opportunities data. This apex
app offers intuitive html form based UI to view, modify or add new opportunities.
• This Quick Analytics App deploys within 10 minutes and offers a rich variety of cross-dimensional analysis
for several metrics.
• Download URLs: http://biappstore.us.oracle.com https://stbeehive.oracle.com/teamcollab/library/st/BICS+Tech+Demos/Public+Documents/Quick+Analytics+Apps/
Copyright © 2014 Oracle and/or its affiliates. All rights reserved.
Getting Started – a sample demo sequence outline
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1. Deploy the application using instructions outlined in readme PDF file
2. Optionally change your demo ASOF date (initial data is as of 1-Nov-2014) See this for more details
3. Demo the dashboards, reports and subject area on Sales Pipeline
Copyright © 2014 Oracle and/or its affiliates. All rights reserved.
Getting Started (contd.)
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4. Navigate to the pipeline apex application and add new opportunities (or modify existing
opportunities) as appropriate.
5. Go back to Dashboards, navigate to ‘Clear BI Server Cache’ dashboard and clear server cache (note:
Cache can be cleared from the BICS modeler UI as well). Review data changes in the dashboards.
Following is screenshots of an example sequence.
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Before any data updates
Adding a new opty from Apex App
After adding a new opty
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Application Screenshots
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Pipeline by Product
Pipeline Overview Trend by Product
Pipeline by Sales Rep
Pipeline by Sales Source
Trend by Sales Rep
Trend by Sales Source
Linear Projection
ASP Track
Aging Analysis
Aging By Customers
Activity level by Sales Rep
Top Customers Pipeline
Win Rates
Opty Editing APEX App
Opties Details
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Overview of opportunities values over time, at various sales stages in the pipeline :
How is the maturity (stages) of my forward-looking pipeline structured? Is it sufficient to sustain business in the coming months? How is the structure month by month based on expected closing date?
Click on any figure or chart to drill into more details
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Expected revenue from Opportunities in various product categories, by sales stages.
Expected revenue is a weight age of total pipeline revenue by opportunity closing probability. Probabilities are entered at each opportunity level, for each stage. This page allows you to understand the breakdown of probable closing revenue by products, over the coming months.
Click on any figure or chart to drill into more details
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Revenue Trend by Products :
How does expected pipeline revenue for coming months align with past month historical closed revenue ? How does this trending compare by product lines?
Click on any figure or chart to drill into more details
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Expected revenue from Opportunities in various product categories, by Sales Reps.
Expected revenue is a weighting of total pipeline revenue by opportunity closing probability, entered at each opportunity level. This page shows the breakdown of probable closing revenue by Sales Reps, over the coming months.
Click on any figure or chart to drills into more details
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Revenue Trend by Sales Reps:
How does expected pipeline revenue for coming months align with past month historical closed revenue ?
How does this trending compare by Sales Reps ?
Click on any figure or chart to drills into more details
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Expected revenue from Opportunities in various product categories, by Sales Sources.
Expected revenue is a weight age of total pipeline revenue by opportunity closing probability, entered at each opportunity level. This page shows the breakdown of probable closing revenue by Sales Sources, over the coming months.
Click on any figure or chart to drill into more details
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Revenue Trend by Sales Sources :
How does expected pipeline revenue for coming months align with past month historical closed revenue ?
How does this trending compare by Sales Sources ?
Click on any figure or chart to drill into more details
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Top customers Pipeline
The aggregation of pipeline for my top customers, and the details of opportunities for each customer
Click on any figure or chart to drill into more details
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Future projection of revenue based on historical revenues from closed Opportunities , expected revenues from Opportunities in the pipeline and overall seasonality of revenues.
Linear regression technique is used to compute the seasonal predictions.
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Detailed report on Opportunities in pipeline
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Aging Analysis of Opportunities in pipeline based on number of days since it was opened.
Track and identify long lasting sales processes by product, by revenue.
Click on any figure or chart to drills into more details
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Aging Analysis of pipeline by customer based on average number of days since opportunities were opened.
Track and identify customer pipeline size by sales cylce time.
Click on any figure or chart to drill into more details
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Average selling price of products by sales owner of those Opportunities
Click on any figure or chart to drills into more details
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Stalled or idle Opportunities (based on days since last activity)
Measure and compare degree of activities of sales Reps on their opportunities.
Identify Reps that have left large opportunities idle without activity for too long.
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Details on idle opportunities
Identify opportunities that have been left idle without any activity on them for too long.
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Analysis of Win rate by territory, product category and trend
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Opty win by sales owner and its trend
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BICS Data Model
The datamodel is built on a single denormalized data table
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‘Sales Opportunities’ apex application allows you to view, modify or add Opportunities.
It also allows you to specify a demo date or date as of which you want to run this app (more details on this is in the coming pages).
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This page displays the list of existing Opportunities and provides the interface to view/modify/add Opportunities.
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Edit any existing Opportunity and change any of its parameters directly
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Add a new opportunity to the dataset.
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This page allows you to setup the app AS OF date.
Out of the box, this whole app including dataset, apex app etc are designed with ASOF date as 01-Nov-2014. Meaning, BI reports, data etc has to be viewed as if your current date is the ASOF date that is setup here. i.e. Imagine you are looking at this on 01-Nov-2014.
When you change this date, all date fields in the dataset will “slide” to align with the new AS OF date. This form calls a DB procedure that makes these data changes.