1. Point of View
Managing Big Data in the
Aerospace and Defense
Enterprise and Supporting the
Vision for Business Insight
“I see in-memory computing changing the game at
our company. Going from several days to seconds
to process this level of granularity gives our
business a competitive advantage. SAP HANA
technology will enable our business leaders to run
their business in real-time.”
- VP of operations for $80B product
development company

2. MANAGING THE BIG DATA CHALLENGE
In-Memory Computing is a relatively new technology that allows the processing of massive quantities of real
time data in the main memory of a server to provide immediate results from analyses and transactions. At
SAP, we are now delivering this capability to the market as a High-performance ANalytic Appliance (aka HANA).
As the CIO at a global manufacturer recently told us, “SAP HANA gives us the tools to instantly perform
complex calculations and forecast the impact in any changes to our business. Traditionally, this is very
difficult to do in a company of our size that deals with diverse channels, dispersed manufacturing and
global product sales of over EUR 9 billion.”
Our aerospace and defense (A&D) clients are telling us loud and clear that the amount of business data is
exploding in their enterprise today. With highly complex supply chains, product lifecycles of 30+ years, end-item
components in one of many product variants often numbering in the tens of thousands, and many of these
components uniquely traceable to a serial number, the challenge of harnessing this data for strategic insight and
operational decision making may at times seem insurmountable. This trend is broadly known as “Big Data.” The
very point of looking at Big Data is to identify
patterns that create answers to questions you did
not even know to ask. What if you could analyze
every transaction, capture insights from granular
data, and did not have to wait for days or weeks to
get information from the field?
With this deluge of information, companies are
essentially mandated to manage unprecedented
levels of information to simply stay competitive.
The challenge, however, is that the information
explosion has or will quickly surpass an
organization‟s ability to effectively harness and manage this data.
Given the volumes and velocity of information, the traditional database
approach is no longer a strategic asset to house and manage information
and drive to differentiated insights. Traditional database technology was
designed for writing transactions resulting in data that is not “stored” in the
way that business users ask questions today. It simply cannot keep pace
with today‟s business requirements for fast and accurate analytical data.
The value of In-Memory technology can be groundbreaking. A significant
portion of the value of In-Memory lies in its ability to open up bottlenecks
and offer users greater access to fresh, granular and accurate data.
Dramatically improved hardware economics and technology innovations in
software have now made it possible for SAP to deliver on its vision of the
Real-Time Enterprise with In-Memory business applications, enabling customers to analyze large quantities of
data from virtually any source in real-time with sub-second response time.
Most organizations struggle with distributed processes, disparate information and unmanageable amounts of
data resulting in reduced customer insight and intimacy, blind spots in the supply chain and operations, missed
revenue opportunities and increased exposure to regulatory risk. Effectively managing Big Data will result in an
organization‟s improved ability to sense changes in the environment and react quickly to trends and data
changes in real-time, supporting a sustainable competitive advantage.
Liability
Supplier Data
Predictive analytics
Billing
Learning curves
Reliability
Alerts
Proposals
EarnedValueManagement
Estimating
Suppliers
Costs
Program Data
Proposals
Parts
Impact analysis
Leadtimes

3. 3
BUSINESS INTELLIGENCE AS A COMPETITIVE ADVANTAGE
Today, data overload and latency in data extraction and analysis are some of the biggest challenges for A&D
companies. There are many risks associated with not fully capitalizing upon the data explosion – business risk,
regulatory risk, and certainly financial risk. But the measures that A&D companies are employing to try to
harvest and mine data are themselves risky and expensive. Here are some examples of typical workarounds:
• Corporate IT tries to optimize existing solutions that are
already complex and highly-customized
• Functional organizations react independently because
they need the data yesterday as they are faced with yet
another fire drill and bet-the-company decision
• Unable to harvest insights from the data, organizations
settle for the “directionally correct” level in making
decisions
• Data is restricted to only a select few business leaders for
fear that exposing larger audiences will only magnify the problem
All of this contributes to higher total cost of ownership (TCO), non-standardized tools across the entire company,
and a business user community that is frustrated by the inability to get the data they need. In addition, big data
drives a considerable increase in storage, hardware, software, and labor costs and makes the management of
these environments complex and expensive. Adding to the challenge, most CIO‟s admit that much of their data
are of poor quality and managers do not trust the information on which they have to base decisions. The
opportunity now exists for organizations to define and implement an In-Memory Business Intelligence strategy
rooted in a single version of the truth. First movers will redefine the competitive rules of engagement and take
market share from „fast followers‟.
SAP‟s In-Memory solution changes the game in terms of data processing volume, speed and cost. It enables
employees at all levels to gather and process very large amounts of information and make decisions in real-time.
Apart from enhanced speed of querying, the In-Memory solution provides users with access to granular level
information unlike in data warehouses that almost always require data to be aggregated to improve query
performance. This provides the user with immense flexibility in querying that can be leveraged to provide much
deeper insights from data.
In-Memory technology has the ability to create more collaboration as Business and IT work to meet information
needs. This results in control over critical information shifting away from those who manage it to the
stakeholders who own and use it. This dynamic will allow all business users to make better business decisions
with higher levels of cascading accountability from the C-Suite to senior management to line management and
end users. This will drive significantly greater business value for the organization as a whole.
A corporate senior vice president at a 5,700-employee company providing high tech services had this to say
about HANA:
 “The product has enabled us to search through 360 million data records in just a little over one
second. This is indeed an incredibly fast speed for this amount of data. Now and in the future,
speed is the key to adapting to an ever-changing business environment. The speed SAP HANA
enables is sudden and significant, and has the potential to transform entire business models.”
The following pages explore in more detail the potential sources of additional value across key A&D business
process areas: Program Management, Manufacturing, Supply Chain Planning, and Aftermarket Services.

4. 4
BUSINESS VALUE AND USE CASES
Program Management
The scrutiny on A&D program managers to improve program affordability and flawlessly execute is intense. As a
core business process in an A&D company for managing the delivery of products and services to customers,
program management can span several years and involve prodigious amounts of complex data. Program
managers today are forced to make key decisions based on information that is out-of-date, not queryable, too
aggregated or simply unobtainable due to complexity or level of manual acquisition effort. The ability to put real-
time information in the hands of program managers and operational executives will keep programs “sold” and
gives the A&D company a competitive advantage.
Sources of Value Value Type Value Definition
Improve decision making  Reduce risk
 Increase
gross margin
Instantly interrogate volumes of internal and external supply chain, manufacturing,
quality, and financial data for program KPIs, evaluate through different dimensions
(e.g., program, customer, product variant, contract) and drill down to root causes.
Detect problem areas early that could erode program profitability and jeopardize
overall schedule
Manage programs to cost
and schedule
 Increase
gross margin
Rapidly simulate multiple scenarios and understand their impact on program cost and
schedule in real time. Scenarios could include any number of variations in demand
signals, supply chain capacity constraints, global events, emergencies, political
outcomes, etc.
Create proposals that will
lead to profitable contracts
 Increase
gross margin
Estimate costs more accurately using detailed analysis of historical data from similar
programs. At the same time, simulate future demand scenarios to assess impacts of
potential programs on each other. Predict production learning curves prior to bidding
to ensure profitability on fixed price contracts.
Manufacturing
Production Operations staff need to be able to analyze the large amount of data from manufacturing, quality and
procurement systems to identify trends and issues before significant costs are incurred and to keep the plant
running at optimum efficiency. Managers want to be alerted with real-time event triggers to potential problems
with manufacturing equipment, settings, processes or embedded components, thereby taking corrective action
quickly. Many manufacturing systems generate large amounts of data that may not be analyzed until after the
fact or is aggregated with the loss of necessary detail to determine what corrective action should be taken.
Sources of Value Value Type Value Definition
Accelerate production
ramp up
 Time to revenue Ramp up production rates predictably. For every new product, the organization needs
to learn new processes, tasks and procedures. The organization can define goals for
learning curves, track progress, understand impact of not meeting defined learning
curves and analyze where efforts should be focused.
Streamline shop-floor
operations
 Increase gross
margin
Analyze manufacturing performance at task level, employee level, work center, plant,
etc. to reveal areas of improvement to target.
Improve product quality  Reduce “cost of
quality”
 Increase gross
margin
Perform real-time root-cause analysis based on detailed granular production data.
Analyze quality issues for trends such as supplier or lot issues and associated costs.
Quickly analyze large complex BOMs and compare EBOM vs MBOM or BOMs of
different variants.
Improve product
lifecycle cost
 Increase gross
margin
Perform detailed analysis of product lifecycle costing from engineering all the way
through aftermarket services. Identify components that erode profitability and mission
effectiveness due to failure and warranty claims.

5. 5
Supply Chain Planning
The typical A&D company has recently experienced a major shift in the degree of outsourcing as well as a
concurrent increase in the complexity and globalization of the supply chain. Marquee programs have recently
overrun initial estimates by billions of dollars due specifically to challenges in managing suppliers and
synchronizing supply and demand. Large amounts of supply, demand and financial data are involved to model
sales and operations planning scenarios. Therefore, with today‟s limitations, only a limited number of scenarios
and limited complexity can be modeled. The objective is to make profitable, fact-based decisions quickly by
considering all relevant information.
Sources of Value Value Type Value Definition
Respond immediately to
changes in supply and
demand
 Increase inventory
turns
 Reduce supply
chain costs
 Improve capacity
utilization
Rapidly simulate multiple supply chain scenarios for better and faster decisions.
Develop operations plans that balance supply chain, manufacturing capacity,
and inventory with customer demand while accounting for a variety of complex
(and frequently changing) demand scenarios, product variants, supplier
constraints and emerging events. Look at cross-site data, leading to better
allocation of site inventory, while optimizing WIP and finished inventory.
Total landed cost analysis  Reduce costs
 Reduce supply
chain costs
Enable real time insight into total landed cost including procurement,
transportation, inventory, overhead, duties, taxes, and fees for all products sold
to customers to enable optimal supply chain decisions. Supports more accurate
sourcing and supply chain network design and plays a significant role in actual
costing.
Product traceability and item
serialization
 Improve
compliance
 Reduce recalls
The A&D industry is struggling with counterfeit parts and the need to track
products from raw material to point of use on large numbers of parts on mission
critical systems. The need is for real-time insights and automated actions with
analytics for efficient execution of traceability and recall scenarios.
Aftermarket Services
In the quest to be a total lifecycle solution provider, most A&D companies are aggressively targeting the market
of service delivery on fielded products. But few business processes are as unpredictable as those associated
with aftermarket service delivery. Much of the solution to this challenge lies in the solution to a Big Data
problem. In-memory computing can analyze services program data combined with vehicle diagnostic data,
asset history and customer information to identify potential program risk areas as well as new business
opportunities.
Sources of Value Value Type Value Definition
Perform predictive
maintenance
 Increased
asset
availability
 Increase
gross margin
 Increase
revenue
Current maintenance strategies that are based on time based replacements or repair
are highly inefficient. Condition based maintenance strategies can offer an efficient
alternative that can have large impact on availability of assets. With the ability to
collect massive amounts of performance data, in-memory computing provides the
opportunity to then apply predictive modeling on top of this to better predict failures
thus improving asset reliability, minimizing failure rates and increasing performance
of SLAs (Service Level Agreements)
Reduce service costs  Cost
reduction
Costs can be reduced through maintenance budget planning and simulation based
on vast amount of performance and MRO data, to include the identification of “bad
actors”
identify up-sell opportunities  Increase
revenue
Increase revenue by quickly identifying up-sell opportunities using in-memory based
applications for customer segmentation, cost & profitability analysis, and service
sales analysis based on customer and asset history

6. 6
HOW READY ARE YOU?
As part of SAP‟s strategic relationship with your organization, we would like to assist in the ongoing formulation
and execution of your Big Data and Business Intelligence strategy by offering participation in a HANA Value
Workshop. Specifically, we would offer to come on site, engage with members of IT and the business to review
HANA solution fit, outline potential use cases based on your priority needs, and identify quick wins. We would
also help you build a business case that quantifies the value of HANA and review this information with executive
sponsors.
As next steps we welcome the opportunity to meet and discuss in greater detail the perspectives shared in this
Point of View and how the HANA Value Workshop could best support your Big Data issues. We look forward to
collaborating with you to shape the your Business Intelligence plan and value proposition focused on harnessing
and managing Big Data to drive significant value for you and your customers.
For further discussions, please contact:
Berry Gibson
A&D Industry Principal
SAP
(412) 297-3313
berry.gibson@sap.com