Reporting at Motorola - Predictive analytics & business insights 2014

transcript

motorola confidential

Reporting at MotorolaPredictive Analytics & Business Insights 2014

http://www.gatewayanalyticsnetwork.com/b122-home

Dr Patrick DeglonDirector of Engineering, Analytics Area Tech LeadMotorola Mobility pdeglon@motorola.com pdeglon

Overview of Motorola Business

About UsMotorola exists to invent, build and deliver the best mobile devices on the planet, improving the lives of millions of people.

Motorola

“Galvin Manufacturing Corporation” created, producing battery eliminators

First walkie-talkie which was vital to Allied communication

“one small step for man, one giant leap for mankind” through a Motorola transceiver

1969 1973 2011 20141986

Invented six sigma quality improvement process

first private handheld mobile phone call; world's first commercial cellular device

world's first handset to combine a Linux operating system and Java technology

Source: Wikipedia

Motorola splits into Motorola Mobility & Motorola Solutions

Key Performance Indicators

Motorola Factory# Shipments

Distribution Channels# Sales

First Usage# Activations

Simplified Business Flow

Data Flow

Motorola Factory# Shipments

Distribution Channels# Sales

First Usage# Activations

Google BigQuery

MotorolaCloud

Insights

• Business overview

• Demos• Daily Activations Report

• Moto Insights

• Drive Insights

Agenda

Daily Activations Report

How to provide a global source of truth and start

to provide insights on data points?

Existing Situation

- Numerous (conflicting) sources of truth- Too many variations of same data cube- “Table in your face” approach- No global business definition- No curation of manually entered data points - Report accessible on an internal portal (through VPN)- No mobile form factor

Demo Daily Report: Final Email

Google: A galaxy of open APIs and Tools… the good, the bad and the ugly

App EngineBig Query

Compute Engine

Users Cloud Messaging

Analytics

Visualization

Data Store

Cloud Storage

Cloud SQL

Translate

Predict

MailData Store

Task QueueMemcache

URL FetchCloud End Point

Channel

JavaPython

Mail and many more ...

Demo Daily Report

● Get data (pivot) from BigQuery

● Spreadsheet magic

● Insights: WoW trends with statistics test, Key driver for growth, Key

milestone, internal QA tests

● Email

● Embedded Chart

● Scheduler

https://docs.google.com/a/motorola.com/spreadsheet/ccc?key=0AgldkCMfisBTdF83VVJqdFVEZFZiZjgyTWJNdzRNblE&usp=drive_web#gid=21

• Assume sales follow a diffusion S-shape, i.e.

Description of the illustrative simulation

Marketing Word of mouth

• Add random noise to theoretical daily activations (Poisson)

• Simulated daily activations (sales) for United States, Canada, Brazil, India, Russia, China, Germany and United Kingdom with various launch date per region

ΔN = a (Nmax - N) + b N (Nmax - N)

Step 1: Create a backbone table

SELECTCAL_DT,Country

ON A.Dummy=B.DummyWHERE

B.CAL_DT>=A.Launch_Date

motorola.com:sandbox:demo.backbone:INNER JOIN (SELECT Country, CASE WHEN Country IN ('United States','Canada') THEN '2013-08-01' WHEN Country IN ('Brazil','Russia','India','China') THEN '2013-10-01' ELSE '2013-12-01' END AS Launch_Date, GDP_USD/1e7 AS Scale, 1 AS DummyFROM [motorola.com:sandbox:pdeglon.countries]WHERE Country IN ('United States','Canada','Brazil','Russia','India', 'China','Germany','United Kingdom')) AS B

(SELECT CAL_DT, 1 AS Dummy FROM [motorola.com:sandbox:pdeglon.calendar]) AS A

Step 2: Calculate KPI value over time

SELECTCAL_DT,Country,

‘Phone 123’ AS Model,INTEGER(Scale*

EXP(-POW( -150,2)/2/POW(75,2))/(75*SQRT(2*PI()))

) AS Daily_ActivationsFROM

[motorola.com:sandbox:demo.backbone]

motorola.com:sandbox:demo.baseline:

DATEDIFF(TIMESTAMP(CAL_DT),TIMESTAMP(Launch_Date))

Normal Distribution:

Step 3: Add Random Noise

SELECTCAL_DT,Model,

Country,INTEGER(

Daily_Activations + SQRT(Daily_Activations) *SQRT(-2*LN(RAND()))*COS(2*PI()*RAND())

) AS Daily_ActivationsFROM

[motorola.com:sandbox:demo.baseline]

motorola.com:sandbox:demo.simulation:

Normal (Gaussian) Random Number (mu=0, sigma=1)

(pseudo) Poisson distribution for N=Daily_activation

Step 4: Final Pivot for report

SELECTCAL_DT,SUM(Daily_Activations) AS Total,SUM(CASE WHEN Country IN ('United States','Canada') THEN Daily_Activations ELSE 0 END) AS NA,SUM(CASE WHEN Country IN ('Brazil','Russia','India','China') THEN Daily_Activations ELSE 0 END) AS BRIC,SUM(CASE WHEN Country IN ('Germany','United Kingdom') THEN Daily_Activations ELSE 0 END) AS EU,SUM(CASE WHEN Country='United States' THEN Daily_Activations ELSE 0 END) AS UnitedStates,SUM(CASE WHEN Country='Canada' THEN Daily_Activations ELSE 0 END) AS Canada,SUM(CASE WHEN Country='Brazil' THEN Daily_Activations ELSE 0 END) AS Brazil,SUM(CASE WHEN Country='Russia' THEN Daily_Activations ELSE 0 END) AS Russia,SUM(CASE WHEN Country='India' THEN Daily_Activations ELSE 0 END) AS India,SUM(CASE WHEN Country='China' THEN Daily_Activations ELSE 0 END) AS China,SUM(CASE WHEN Country='Germany' THEN Daily_Activations ELSE 0 END) AS Germany,SUM(CASE WHEN Country='United Kingdom' THEN Daily_Activations ELSE 0 END) AS UnitedKingdom

FROM[motorola.com:sandbox:demo.simulation]

WHERECAL_DT<CURRENT_DATE()

GROUP BY 1ORDER BY 1 DESC

Demo Daily Report: New Menu Item

Demo Daily Report: Edit Code (App Script)

Demo Daily Report: Example for adding a new menu item

Demo Daily Report: Key Query (pivot)

Demo Daily Report: Running the query

Demo Daily Report: Parsing the results

Demo Daily Report: Data Sheet

Demo Daily Report: Summary sheet

Demo Daily Report: Preparing email

Demo Daily Report: Email template sheet

Demo Daily Report: Preparing email

Demo Daily Report: Sending email

Demo Daily Report: Signal vs Noise and Main Drivers

Demo Daily Report: Key Milestones

Demo Daily Report: Final Email

Demo Daily Report: Scheduling

• Moto Insights

• Drive Insights

Agenda

Moto Insights

How to provide insights to executive-on-the-go with a

robust system where new report take seconds to create?

Existing Situation

- Require VPN- New Report take weeks- New features take months- Issue Tickets come weekly

Demo Moto Insights

Moto InsightsApp Engine

Data Source:Big Query

ReportMeta Data:Datastore

Tracking:Datastore

Users Access:Google Users

(email) +Datastore (role)

Moto InsightsWeb portal

Moto Insights Android App

Demo Moto Insights: Main menu & Responsive Design

responsive design

Demo Moto Insights: Report Details

Demo Moto Insights: 1st Chart Details

Demo Moto Insights: Chart Types

Demo Moto Insights: Dummy Example

• Moto Insights

• Drive Insights

Agenda

Drive Insights

How to democratize Analytics within the company while

maintaining quality (data & insights) as well as maintain Big

Data usage under control?

Existing Situation

- Reports are produce by a centralized team- Role management is becoming out of control- Product teams are complaining to have to run SQL repeatedly on BigQuery console

Demo Drive Insights (v2)

Drive InsightsApp Engine

Data Source:Big Query

Data Source:Google Analytics

iFrame Source:Tableau Server

iFrame Source:Google Documents

Data Source:Spreadsheet & CSV

ReportMeta Data:

Google Drive

(Text file with JSON)

Report Meta Data:Datastore

(Report copy & usage tracking)

Users Access Control:

Google Users + Drive Sharing

Google Drive

Moto Insights Android App

Drive InsightsWeb portal

Demo Drive Insights: New document type

Demo Drive Insights: Report creation

Demo Drive Insights: 1st Chart Details

Demo Drive Insights: 2nd Chart Details

Demo Drive Insights: Chart Types

Demo Drive Insights: SQL Editor (CodeMirror)

Demo Drive Insights: Report document in your Google Drive

Demo Drive Insights: Dummy Example

Demo Drive Insights: Drive Sharing

?Dr Patrick DeglonDirector of Engineering, Analytics Area Tech LeadMotorola Mobility pdeglon@motorola.com pdeglon

In this presentation, Patrick Deglon will share his learnings and provide best practices when using open Google tools & API. He will present his daily email report that hundreds of key Motorola stakeholders are receiving to drive the business, as well as a mobile solution based on the latest web technologies, including Google Visualization, Bootstrap CSS and many of the Google APIs (Gmail, BigQuery, Analytics, Drive, App Engine, Users authentication, etc.).

Abstract

Dr Patrick DeglonDirector of Engineering, Analytics Area Tech LeadMotorola Mobility

With a PhD in Particle Physics, Patrick Deglon spent the last decade driving business insights at eBay and at Motorola Mobility, a Google company.At eBay, he led significant improvements in marketing effectiveness by developing methods to measure incremental sales, and by running large scale experiments on Internet marketing channels.

He joined Motorola Mobility in 2013 to help raise the bar in Analytics and on-board open Google tools and technologies. He is now the Area Tech Lead for Analytics within the Cloud Services organization.

He is married with two kids and enjoys his town of Campbell, CA.

Reporting at Motorola - Predictive analytics & business insights 2014

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