in memory computing for agile business intelligence

management|consulting

IN-MEMORY COMPUTING FOR AGILEBUSINESS

INTELLIGENCE

Dr. Markus Alsleben CEO Alsleben Ltd.


AGENDA

Self Introduction

Trends in the Global IT industry

The Pretense of Knowledge

The Journey towards In Memory

Computing

Introducing SAP Hana - In Memory

DB

SAP Hana - Live Demonstrations

Q&A


COMPANY INTRODUCTIONFounded in 2008 by Dr. Markus Alsleben, Alsleben Ltd. provides management consulting and professional services critical for companies engaging in the high velocity Chinese marketplace.

At Alsleben Ltd. we believe that quality advisory in the context of high velocity environments can only be successful through a solid scientific foundation. Management research projects are therefore an integral part of our practice incorporating latest research into unique client solutions. Our affiliation with prestigious research institutions and corporations enables us to utilize the latest knowledge base for your management consulting projects with Alsleben. Ltd. implementing next practice today.

Our services include:

•Management Consulting and Training Services: Since 2008 Alsleben Ltd. has worked together with leading multinational companies across various industries in China and around the world to design and implement strategies, change organizations and conduct training services that deliver results.

•Information Technology Advisory: Business without powerful IT support is impossible in today's hyper competition. Designing and implementing IT Strategies and ERP Systems provides the competitive edge sustainable success for your China operations.

•Human Resources: World-class talent acquisition and management are key capabilities of successful enterprises in China. Alsleben Ltd. provides talent management solutions that let you win the war for talent in China.

Dr. Markus AlslebenCEO Alsleben Ltd.

Affiliations Selected Clients


BIO

2008 - today

CEOAlsleben Ltd.Management Consulting, Hong Kong

2008 - 2010

Lead Management ConsultantLocation Strategy & Management Project Designing and Implementing SAP's global Location Strategy. Spatial reorganization and optimization of R&D at SAP.

SAP AGGermany

2006 - 2008

Vice PresidentCorporate development and execution of growth strategy for development locations in China.

SAP Labs ChinaShanghai

2000 - 2006

Vice President - Consulting Director North AsiaConsulting head for Greater China with more than 150 consultant, delivering SAP implementations.

SAP ChinaBeijing

1997 - 1999

Senior SAP Consultant for Logistics

KPMG Consultingnow Bearing Point & o.tel.o Telecom, Germany


SAP: Establishing a Research Centre in China

Harvard Business Publishing - Case Study

PUBLICATIONS

Creating Dynamic Capabilities

R&D Network Management for Globally Distributed Research and Development in the Software Industry


TRENDS IN THE GLOBAL IT INDUSTRY

management|consultingmanagement|consulting

GLOBAL IT TRENDS - HYPE CURVE

Source: Gartner, 2012.

Big Data

Cloud

Mobile


GLOBAL IT TRENDS

CLOUDCOMPUTINGCloud computing provides “convenient on-demandnetwork access to a shared pool of configurable computing resources that can be quickly provisioned and released with minimal management effort or service provider interaction.”1 The various subsets of could computing as SaaS, PaaS, Iaas or more generic XaaS provide cost effective and high available computing resources with near to unlimited scalability.

BIG DATAThe exponential growth in data across all industries requires new technologies for:

• Data Sourcing and Storage

• Data Analysis and Classification

• Data Integration and Transformationto generate new

insights and opportunities.

MOBILE COMPUTINGThe increasing penetration of connected mobile phones and tablet computers allows new context based services as e.g. location based services, augmented reality and rapid data collection e.g. for traffic analysis. Always on mobile devices allow quick communication and collaboration. By 2013, more than 15 billion devices will be connected to the Internet using a mobile device.

1Source: Mell, p. and Grance, t. the nIst definition of cloud computing. Special Publication 800-145, 2011; http:// csrc.nist.gov/publications/nistpubs/800-145/sp800-145.pdf


CLOUD COMPUTING HYPE CURVE 2012


10n

Prefix 10n Decimal Scale

0 1 one

deca 110 ten

hecto 2100 hundred

kilo 31,000 thousand

mega 61,000,000 million

giga 91,000,000,000 billion

tera 121,000,000,000,000 trillion

peta 151,000,000,000,000,000 quadrillion

exa 181,000,000,000,000,000,000 quintillion

zetta 211,000,000,000,000,000,000,000 sextillion

yotta 241,000,000,000,000,000,000,000,000 septillion

4k MemoryApollo

Guidance Computer

2.5 Petabyte Wallmart’s annual

Data Growth

7.9 Zetabyte

est. amount of digital data by 2015

295 Exabyte estimated complete human

knowledge in 2007

1 Terabyte equals

210 single sided DVDs

880 Yottameterdiameter of observable universe


BIG DATA IS NOT ONLY BIG...

Source: SAP 2012.


Source: SAP 2012.

Business Rational of Mobile Enterprise Computing


A day in the life with mobile analytics suite

Source: SAP 2012.


THE PRETENSE OF KNOWLEDGE

Herbert A. SimonFriedrich August Hayek Nassim Nicholas Taleb


v

“It seems to me that this failure of the economists to guide policy more successfully is closely connected with their propensity to imitate as closely as possible the procedures of the brilliantly successful physical sciences - an attempt which in our field may lead to outright error. [...]

Unlike the position that exists in the physical sciences, in economics and other disciplines that deal with essentially complex phenomena, the aspects of the events to be accounted for about which we can get quantitative data are necessarily limited and may not include the important ones.

While in the physical sciences it is generally assumed, probably with good reason, that any important factor which determines the observed events will itself be directly observable and measurable, in the study of such complex phenomena as the market, which depend on the actions of many individuals, all the circumstances which will determine the outcome of a process, for reasons which I shall explain later, will hardly ever be fully known or measurable. [...]

[Using Mathematical techniques] has led to the illusion, however, that we can use this technique for the determination and prediction of the numerical values of those magnitudes; and this has led to a vain search for quantitative or numerical constants.”

Friedrich August HayekNoble Laureate in Economics 1974

SOURCE: http://www.nobelprize.org/nobel_prizes/economics/laureates/1974/hayek-

lecture.html

SOCIAL SCIENCE ≠ PHYSICAL SCIENCE

QUANTITATIVE RESEARCH

QUALITATIVE RESEARCH

MIXED-METHODSRESEARCH


Herbert A. Simon

v

BOUNDED RATIONALITY

SATISFYICING

POLITICAL BEHAVIOR

In Economics the so called Neoclassical school postulated rational decision making of the “homo oeconomicus” with perfect information available.

Uncertainty about the future and costs in acquiring information in the present were not considered part of rational decision theory. However do uncertainty and costs limit the extent to which agents can make a fully rational decision, thus they possess only “bounded rationality” and must make decisions by “satisficing,” or choosing that which might not be optimal but which will make them happy enough.

The internal organization of firms and the external business decisions thereof did not conform to the Neoclassical theories of “rational” decision-making. Bounded rationality is used to designate rational choice that takes into account the cognitive limitations of both knowledge and cognitive capacity. Bounded rationality is a central theme in behavioral economics. It is concerned with the ways in which the actual decision-making process influences decisions. Theories of bounded rationality relax one or more assumptions of standard expected utility theory”.

BOUNDED RATIONALITY: “I KNOW THAT I DON’T KNOW”

SOURCE: WIKIPEDIA.ORG


Nassim Nicholas Taleb

v

LUCID FALLACY

HINDSIGHT BIAS

DON’T BE THE TURKEY

SH.... HAPPENS

SURPRISESURPRISE



Until 1697 all known Swans were white, so that the existence of a black swan was considered impossible, until the discovery of Australia and with it the discovery of black swans.

Nasim Nicholas Taleb defines a black swan event as a surprise (to the observer), one that has a major effect, and after the fact is often inappropriately rationalized with the benefit of hindsight explaining:

•The disproportionate role of high-profile, hard-to-predict, and rare events that are beyond the realm of normal expectations in history, science, finance, and technology

•The non-computability of the probability of the consequential rare events using scientific methods (owing to the very nature of small probabilities)

1.The psychological biases that make people individually and collectively blind to uncertainty and unaware of the massive role of the rare event in historical affairs

Mitigation strategies

• Built robustness agains black swan events, exploit white swan events• Avoid modeling based on normal distributions as risk is typically NOT normal distributed !• “Avoid being the Turkey” - turn around black swan into white swan events.

v

LUCID FALLACY

HINDSIGHT BIAS


“Fat Tail Distributions”

SH.... HAPPENS

SOURCE: WIKIPEDIA.ORG



v

LUCID FALLACY

HINDSIGHT BIAS


“Fat Tail Distributions”

SH.... HAPPENS

Then one morning Deadalus said to Icarus:Then one morning Deadalus said to Icarus:

““Now Son, we are ready to leave this island for good. Now Son, we are ready to leave this island for good. We shall fly home to Athens. But although you are We shall fly home to Athens. But although you are now quite good at flying, you must not forget that it now quite good at flying, you must not forget that it can be very dangerous. So listen to my instructions can be very dangerous. So listen to my instructions and be sure to follow them to the letter. At all times and be sure to follow them to the letter. At all times follow me, for I will find the way home. Do not veer off follow me, for I will find the way home. Do not veer off on a different flight path, or you will soon be lost. And on a different flight path, or you will soon be lost. And do not fly too low, or your wings will fill with moisture do not fly too low, or your wings will fill with moisture from the waves and they will become too heavy you from the waves and they will become too heavy you will sink down. Nor should you fly too high, or the sun will sink down. Nor should you fly too high, or the sun will heat the wax and your wings will fall apart. Have will heat the wax and your wings will fall apart. Have you understood all that I have said?you understood all that I have said?””


Kathleen Eisenhardt

v

POLITICAL BEHAVIOR

RESOURCE ALLOCATION

PROCESS

DYNAMISM

Clay Christensen

Political behavior is an important contingency in enterprises. Strategic

Management is not a mere planning problem as intended strategies are

often not implemented as planned and deliberate strategies emerge

over time.

Resource Allocation Process

SOURCE: Christensen, C. M. & Dann, J. B. (1999). Process of strategy definition and implementation. Harvard Business Publishing.

Eisenhardt, K. M. & Bourgeois, L. J. B. (1988). Politics of strategic decision making in high-velocity environments: Toward a midrange theory. Academy of Management Journal, 31(4), 737-

770.

Schreyögg (2008). Organisation - Grundlagen moderner Organisationsgestaltung [Organization - Foundations of modern organizational design] (5th Edition ed.). Wiesbaden: Gabler.

Preconditions of political processes:

•diverging interests among organizational members

•limited amount of resources available to satisfy all such

interests.

•Decisions with non-determined outcome

•The larger the available decision space the more political

decisions tend to become, as outcomes require coalitions,

negotiations and tactics between participants in the political

process.

While political processes typically negatively correlate with

profitability in high velocity environments, they can be a

source of corporate renewal that leads to higher

profitability.

SOLID DATA IS NOT EVERYTHING


The Journey

towards In-

Memory

Computing


THE ROAD TO IN-MEMORY COMPUTING

George E. Moore

SOURCE: SINGULARITY.COM


“Relational database systems have been the backbone of business applications for more than 20 years. We promised to provide companies with a management information system that covers the core applications, including financials, sales, order fulfillment, manufacturing, as well as human resources, which run from planning through business processes to individually defined analytics. Hasso Plattner

ORIGINS OF OLTP AND OLAP

However, we fell short of achieving this goal. The more complex business requirements became, the more we focused on the so-called transactional processing part and designed the database structures accordingly. These systems are called OLTP (Online Transactional Processing) system. Analytical and financial planning applications were increasingly moved out to separate systems for more flexibility and better performance. These systems are called OLAP (Online Analytical Processing) systems.”

Plattner, H. (2009). A common database approach for oltp and olap using an in-memory column database. In Proceedings of the 35th sigmod international conference on management of data.


ERPERPSupplier

Relationship Management

(SRM)

Supplier Relationship Management

(SRM)

Customer Relationship Management

(CRM)

Customer Relationship Management

(CRM)

Advanced Planner & Optimizer

(APO)

Advanced Planner & Optimizer

(APO)

Business Warehouse

(BW)

Business Warehouse

(BW)

Logistics ExecutionLogistics Execution

Mobile PlatformMobile

Platform

SAP’s product landscape circa 2000 - 2005


Architectural Benefits(+) Performance due to dedicated system(+) Independent / No single point of failure

OLTP - THREE TIER ERP SYSTEM OLAP - DATA WAREHOUSE SYSTEM

Architectural Challenges(-) More Expensive through additional hardware(-) Double work for data cleansing, uploading, cube design, report writing(-) Upload Windows often not sufficient in large scale installations.

OLTP AND OLAP ARCHITECTURES

Adopted from: Plattner, H. & Zeier, A. (2012). In-Memory data management: Technology and applications. Springer

Data Cubes


v


USER EXPECTATIONS HAVE CHANGED

Source: google-classic.com

“At the University of Potsdam, I got bored with the presentation of traditional enterprise software and the students didn't like it much, either; they wanted something more modern, more like Google.” Hasso Plattner

Traditional Business Analytics

In-Memory Business Analytics


TRADITIONAL DATA WAREHOUSE VS. IN-MEMORY ANALYTICS

NEW WAYNEW WAY

SOURCE: SAP

OLD WAYOLD WAY


SOURCE: http://www.codinghorror.com/blog/2008/07/maybe-normalizing-isnt-normal.html

Normalized Database Form (De-)Normalized Database FormFlat File

WHY DO WE NORMALIZE AT ALL ?


Plattner, H. & Zeier, A. (2012). In-Memory data management: Technology and applications. Springer

SAP HANA - HIGH LEVEL ARCHITECTURE


COLUMNAR VS. ROW BASED STORAGE

Source: Plattner, H. & Zeier, A. (2012). In-Memory data management: Technology and applications. Springer


TECHNOLOGIES BEHING IMDB



SOURCE: Plattner, H. (2009). A common database approach for oltp and olap using an in-memory column database. In Proceedings of the 35th sigmod international conference on management of data.

Current Table Structure in SAP ERP Finance

Accounting Document Header

Accounting Document Items

Future Table Structure in SAP ERP Finance (Vision)

IMDB: RADICALLY SIMPLIFYING ENTERPRISE APPLICATIONS (e.g. SAP ERP FINANCIALS)



BUSINESS BENEFITS (TCO)On the fly financial aggregation, e.g. closing according to different accounting standards (US-GAAP, IAS, etc), financial applications faster and less complex. Provision of on-demand scenarios and analytics allow frequent run of simulations and establish higher business agility.

Simplification of overall IT landscape (one application server instead of server farm with dedicated application servers) resulting in less power consumption, cooling etc. - The solution is easier to setup, scale and change.

Less complex software, through reduction of software layers resulting in less maintenance and administration costs.

Allows the creation of innovative business solution for on the spot decision making that were previously not feasible - online personalised discounts.


DYNAMIC CAPABILITIES

Competitive Advantage based on organizational resources or capabilities is not sustainable in high velocity environments, Dynamic Capabilities thus become a critical differentiator for successful global enterprises.

Micro-foundations of Dynamic Capabilities (Teece, 2009, p. 49)

Source: Teece, D. J. (2009). Dynamic capabilities and strategic management. Oxford: Oxford University Press.


Case Study: SAP Location Strategy & Management


[email protected]

THE FUTURE OF DATA DRIVEN MANAGEMENT: THE MANAGEMENT COCKPIT

SOURCE: Controlling - Zeitschrift für die erfolgsorientierte Unternehmensführung, Vol. 18, June 2006, p. 311-318


SOURCE: Controlling - Zeitschrift für die erfolgsorientierte Unternehmensführung, Vol. 18, June 2006, p. 311-318


INTRODUCING

SAP HANA

IN MEMORY DB


SAP HANA

Live Demonstrations


http://www.saphana.com/welcome

YOUR PERSONAL SAP HANA CLOUD DEMO

SAP HANA VISUAL INTELLIGENCE

HANA Studio


YOUR PERSONAL SAP HANA CLOUD DEMOHow to get access to your personal SAP Hana Test Drive System?

1) Sign up with the SAP Community Network (SCN) at http://scn.sap.com/welcome


YOUR PERSONAL SAP HANA CLOUD DEMO

2) Navigate to http://scn.sap.com/docs/DOC-28191, read the document and sign up via the link at the bottom of the page

3) Accept the T&Cs 4) Confirm you data5) Follow the instructions you have received in your email



Now it’s your turn... SAP HANA Web access

PROFITABILITY ANALYSIS SALES COCKPIT

CENSUS DATA WITH GIS INTEGRATION



Use Case: Profitability Analysis

PROFITABILITY ANALYSIS

Profitability Reports in the SAP ERP Controlling Module (CO-PA) are what managers are most interested in to analyze profitability, over time, by region, product group and customer segments.

Traditionally these reports have a very long run time in large enterprises.

This web based example shows the CO-PA Accelerator in which CO-PA data structures are copied into Hana.

This web based example with a real backend Hana systemallows account manager, regional sales manager and sales director to review critical profitability information.



Use Case: Sales Cockpit

SALES COCKPITRegular reviews of the Sales Pipeline and analysis of sales performance are critical for Sales Executives to safeguard revenue generation for the enterprise.

Recent data is critical for territory planning, account reviews and definition and implementation of marketing strategies.

Traditionally this data resides in SAP CRM and reports have a very long run time in large enterprises. This web based example with a real backend Hana

systemallows to assume the roles of senior sales director and vice president of sales reviewing sales pipeline and sold revenue.



Now it’s your turn... SAP HANA Web access

CENSUS DATA WITH GIS INTEGRATION

Governments all around the world need accurate data for provision of public services, benefits, taxation and infrastructure.

This SAP Hana application combines the power of in-memory computing with a Geographical Information System to immediately visualize census data with changes of the map. It also allows the analysis and breakdown of census data by various dimensions.

This web based example with a real backend Hana systemallows to analyze annonymised real US Census data in a geographical context.


TYPICAL DBA

REQUIREMENTS

QUESTIONS &

ANSWERS


THANK YOU