Proctor & Gamble – Business Sphere and Decision Cockpits

“In the struggle for survival, the fittest win out at the expense of their rivals because they succeed in adapting themselves best to their environment.” With this quote,  Charles Darwin clearly defined today’s business analytics imperative.

 

In this posting we illustrate a best-in-class Analytics Innovation Case Study at P&G. The case study illustrates the way Business Analytics is becoming more central as retail and CPG decision making speeds up. 

 

P&G Overview

P&G’s has 127,000 employees and 300 brands sold in 180 countries.  P&G averages about 4 billion transactions daily. P&G CEO Bob McDonald has staked out a strategy to “digitize” the company’s processes from end to end, and Business Sufficiency, Business Sphere and Decision Cockpits is enabler of that agenda. 

 

P&G is building analytics expertise at a time when P&G is cutting costs in other areas, including eliminating 1,600 nonmanufacturing jobs. The company’s IT organization itself has cut $900 million in total spending over the past nine years.

 

P&G is investing in analytics talent, even as the company cuts in other areas, to speed up business decision making.  True leaders develop the capabilities required for making good and timely decisions in unpredictable and stressful environments. 

Mobile BI – Business KPIs and Dashboards “on-the-go”

Who doesn’t want to achieve faster “time-to-information” and shorter “time-to-decision” for executives and managers with mobile BI?  Who doesn’t want to disseminate insights or KPIs to front-line employees, such as field sales representatives, line of business managers, and field service employees?

The question is not whether Mobile BI is a good idea but how to execute this program in a low-cost way?  How to design and deploy eye-popping “wow” apps? How to support, maintain and enhance these apps which are constantly changing?  What technology and infrastructure to put in for a national or global deployment? Who is going to fund all this plumbing – corporate, LoB or IT?

Business Analytics solutions for “always-on” 3/4G enabled mobile devices – iPads, iPhones, tablets, smart phones – are becoming prevalent as the form factor becomes appropriate for BI.   We are increasingly seeing firms build state-of-the-art dashboard solutions for iPads. The “post-desktop” apps provide senior management with intuitive interactive access to the company’s most important business KPIs and dealing with data overload.

Tablets, 4G Wireless and next gen displays (+gesture based, verbal interfaces) have enabled new productivity improvements and better ways to consume information, perform ad-hoc querying and scenario planning. Dashboard, heatmaps and scorecards on the iPad, iPhones and Androids are intuitive, attractive, powerful, available at any time and any place: a perfect mix for top managers, sales teams and even customers.

BI (and Information Management) is a natural fit for mobile devices.  Managers, blue and white workers spend a majority of their time away from their desks. Most are traveling, walking about or driving from site to site. And it’s these mobile workers who need the most up-to-date information. They need mobile BI to retrieve data to make on-the-spot decisions, monitor operational processes and review KPI, and work-in-process dashboards.

Apple iCloud Service – Lessons for “Big Data” and BI Architects

Apple with its iCloud offering is attacking the consumer facing digital content big data problem. Big Data is challenging on many fronts from the insights (e.g., analytics and query optimization), to the practical (e.g., horizontal scaling), to the mundane (e.g., backup and recovery).

On June 6th, 2011 Apple Inc. launched its new purpose built digital locker service called iCloud for its 225 million iTunes accounts that frees the end-user from the tyranny of the device.  The iCloud service is a cloud offering that would allow users to store digital files such as photos, MP3 music, videos and documents in the cloud and access them from Internet-connected devices like iPhones, iPads, iPods, iMacs and others.  

So, what’s the big deal? They are addressing a classic BI data management problem:   How to free up data trapped in “device and  application jails” in a user-friendly way. The “scan and match” concept   is quite applicable to large scale Enterprise Datawarehouses which suffer from data integrity issues as edge data capture and consumption devices proliferate.

Data ingestion, governance and management is a huge problem facing large organizations.  As data volumes double every year, not having a basic data management strategy will become an Achilles heel. Most organizations unfortunately don’t know what data assets they have, where these assets are, how they are organized and how well they are secured.  Apple shows a neat way to address the Big Data problem in personal cloud management.

Gartner says – BI and Analytics a $12.2 Bln market

The term “business intelligence” (BI) dates back to 1958, when IBM researcher Hans Peter Luhn coined the term in an IBM Journal article.

However, it took until 1980s when decision support systems (DSS) became popular and mid 1990s for BI started to emerge as an umbrella term to cover software-enabled innovations in performance management, planning, reporting, querying, analytics, online analytical processing, integration with operational systems, predictive analytics and related areas.

BI, Analytics [and Big Data] Market Sizing