Description
How Small and Midsize Enterprises Can Sharpen Performance with Next Generation Business Intelligence and Analytics
WHI TE PAPER
How Smal l a nd Mi ds i z e Ent er pr i ses Ca n Shar pe n
Per f or ma nc e wi t h Ne x t - Ge ne r a t i on Bus i ness I nt e l l i gence
a nd Ana l yt i c s
Sponsored by: SAP
Dan Vesset Raymond Boggs
October 2012
EXECUTI VE SUMMARY
Small and midsize enterprises (SMEs), which IDC defines as having fewer than 1,000
employees, have been especially challenged by the changing world economy, new
competitive pressures, and the increasing pace of business in general. As the
digitization of a growing number of business processes continues, many SMEs are
finding a growing need to leverage customer, operational, and financial data for better
decision making. Unlike large enterprises, which have extensive technology and other
resources to draw on, SMEs are limited in the extent to which they can leverage the
latest technology to measure current performance and uncover new insights to help
improve interactions with customers or suppliers, to introduce new products or
services, and to optimize operations. The latest generation of in-memory database
(IMDB) technology — such as the SAP HANA platform — and applications deployed
on it are providing SMEs with effective capabilities with attractive return on investment
(ROI) and total cost of ownership that will improve business decision making,
competitive positioning, and long-term business success.
For SMEs, there may be a sense that management tools are already satisfactory for
running the business. Regular reporting mechanisms have worked in the past, and
formal planning for the future is often considered an exercise in extending the trend
lines from recent quarters. In truth, though, the capabilities that firms used in the past
are simply inadequate for today's fast-moving business environment. Relying on
monthly or quarterly sales results to gauge business success and develop plans is
like driving down a dark highway using just a rearview mirror. The approach is far
more risky than using headlights to judge the shifting conditions of the road ahead.
Real-time results, provided through business intelligence (BI) and analytics
technology, can provide management with the kind of information needed to evaluate
business health (descriptive) but also judge the value of potential alternative courses
of action (predictive). The latter is far more important in the long term and is
associated with the two critical attributes of the most successful companies: agility
and flexibility. While the investment in business intelligence resources should be
justified on the basis of performance improvements, the real value will be far greater:
identifying new business opportunities that will enhance a company's long-term
growth prospects. In effect, IT management should make the case for investment
based on the tangible financial benefits that can be achieved in the short term, but
general management should appreciate (and be excited by) the windows to new
opportunities that effective BI and analytics will open.
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The sections of this IDC white paper are organized around key topics to pave the way
for an effective implementation of a new generation of BI and analytics solutions:
? Business Analytics Best Practices: What can we learn from others?
? Business Analytics Requirements and Pain Points: What are the "must have"
capabilities and the "must avoid" pitfalls in implementation?
? In-Memory Database as a Platform for a New Generation of Analytic and
Operational Applications: How is new technology making a difference?
? SAP HANA Platform: SAP in-memory computing technology use case with a
discussion of both business benefits and IT benefits.
? Challenges and Opportunities: A list of categories that you will need to be aware
of and potentially address.
? Recommendations: Business managers and IT managers will have different
concerns, and you should make sure you understand the position of others.
? Conclusion: Information delivery can be a challenge for organizations because of
the changing nature of the data, but their ability to address this challenge will be
increasingly important for business success.
BUSI NESS ANALYTI CS BEST PRACTI CES
In today's global economy, success in the form of better performance is increasingly
defined by having the freedom to innovate, to provide customers with better products
and services, and to act faster and with greater insight within ever-shorter decision
windows in the face of uncertainty within a rapidly evolving economic system.
There is growing quantifiable evidence that organizations with higher business
analytics competency outperform their less analytically oriented peers. IDC research
shows that most analytically oriented organizations are 20% more likely to be among
the most competitive organizations within their industry.
Today, access to information, combined with the ability to analyze and act upon that
information, creates competitive advantage in commercial transactions, enables
sustainable management of communities, and promotes appropriate distribution of
social, healthcare, and educational services.
The information access, analysis, and management challenges of the intelligent
economy can overwhelm SMEs that are unprepared for the emerging changes. While
many will manage through the process, they will find things far more challenging than
SMEs that anticipate and plan for their changing information needs. IDC defines the
former group of reactive organizations as "fumblers" and the latter group as "fact
finders." As described in IDC's study Analytical Orientation and Competitiveness: The
Difference Between Fact Finders and Fumblers (IDC #223408, May 2010), "fact
finders" are organizations that have the highest levels of the following characteristics:
©2012 IDC #237342 3
? Reliance on analytics, which is defined as the degree to which the manager
relies on analytics (as opposed to experience or intuition) for decision making
? Influence on actions, which is defined as the extent to which the output of the
organization's business analytics solutions influences all employees' actions
? Criticality to competitiveness, which is defined as the perceived level of
criticality of the business analytics solutions to the organization's competitiveness
? Effectiveness of analysis on decision making, which is defined as the
importance of the organization's business analytics technology and processes in
helping improve individual decision making or in facilitating intragroup or
intergroup decision making
Our research demonstrates that, as a group, fact finders are more competitive within
their industries (see Figure 1).
F I GURE 1
An al y t i c a l Or i en t at i o n o f L e a d e r s Ver s u s L a gg a r d s
Source: IDC, 2012
80% of leaders (most competitive organizations in their industry) are fact finders
(have a higher level of analytical orientation), while only 58% of laggards (least
competitive organizations) are fact finders (see Figure 2). In other words,
organizations that are more competitive within their industries have higher levels of
analytical orientation.
While being a fact finder does not ensure success, competitive differentiation —
based on the application of analytics for ad hoc analysis, discovery, or planning
processes and embedded into other business applications — will continue to make a
difference for many SMEs.
Fact Finders
Fact Finders
Fumblers
Fumblers
0% 20% 40% 60% 80% 100%
Leaders
Laggards
(% of respondents)
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BUSI NESS ANALYTI CS REQUI REMENTS AND
PAI N POI NTS
Executives, managers, and other decision makers at SMEs want the most relevant,
timely, and accurate information to enable better decision making. Over 40% of SMEs
plan to make BI and analytics technology available to more executives as well as
power users, including managers and analysts.
SMEs want the right tools that will provide this information to them. Forty percent of SMEs
rank BI and analytics as a high or very high priority investment for their organizations.
Additionally, more SMEs increasingly consider BI and analytics tools mission critical. Sixty
percent of SMEs state that if their BI and analytics solution were out of service by up to
one day, it would have a material negative impact on business operations.
1
Yet, adoption of BI, analytics, and data warehousing technology among SMEs is relatively
low. Only 10% of SMEs state that there is widespread reliance on BI and analytics on a
daily or ongoing basis.
2
Only 13% say they have a relational data warehouse today.
1
What is keeping SMEs from embracing the latest tools? From one recent IDC survey, the
top three areas that SMEs would most like to see improved in their BI and analytics
solutions are flexibility in accessing, analyzing, and manipulating data; intuitiveness of the
user interface; and frequency of data updates.
1
From another survey, the top three areas
that SMEs would most like to see improved in their BI and analytics solutions are data
visualization, ability to do scenario evaluation or what-if analysis, and generally faster
response time to queries.
2
In each case, the message is clear — users want more
flexibility, self-service, and real-time access to information. Having increasingly become
accustomed to real-time access to relevant information in their personal lives, employees
expect the same in their workplaces. Decision makers at SMEs expect to have access to
information at decision time, which may mean access via a mobile device or embedded in
operational applications. Speedy decision making based on real-time information
presented in a clear and compelling way can help drive company success.
Yet, self-service capabilities for BI and analytics users at SMEs lag behind those of large
enterprises, and 20% of SMEs provide no self-service functionality to their business users.
It is a reasonable assumption that this stems from substandard system performance,
which requires IT to keep full control of the technology and to focus on prebuilding rigid
user interfaces and data models, which, in turn, have lengthy internal development cycles,
to address any new user requirements.
2
Only a quarter of SMEs agree that the speed of
their IT department's response to BI and analytics requests meets end-user expectations.
3
SMEs, like their larger counterparts, increasingly need to deal with a broader set of
data sources and types. The spectrum of data that SMEs report capturing besides
transactional data includes text from non–social networking sources (e.g., email,
forms, surveys), chatter from social networks, GIS data, Web logs, machine-
generated data from sensors, audio, and video. While some data types, especially
audio and video, require highly specialized transformation software to make the data
usable by analytic tools, it is increasingly a requirement for business analytics
solutions to be able to integrate data of multiple types and structures. Data integration
is the second most frequently cited BI and analytics challenge for SMEs, trailing only
the cost of the technology.
©2012 IDC #237342 5
IT tools and their functionality are a key part of the issue, but so is staffing. Most
SMEs do not have the dedicated experts in business analytics software to design and
develop a data warehouse, data marts, multidimensional cubes, and a variety of end-
user interfaces ranging from reports and dashboards to business process and
industry-specific analytic applications. Insufficient specialized IT skills are the third
most frequently cited BI and analytics challenge among SMEs.
1
Often, business analysis and decision making are done using managed data
structures such as data marts or analytic cubes, which, in turn, are fed from data in an
enterprise data warehouse or operational data sources of various kinds. Building or
refreshing these structures takes time and staff resources and usually must be
scheduled in advance. The problem is that business issues can arise suddenly and
requirements can change quickly, and a system too slow to react to business
changes can derail the achievement of business goals.
Many managers and analysts resort to getting subsets of data in one way or another and
often build their own spreadsheets rather than rely on IT to build the structures they need.
As a result, they sometimes base key decisions on data that is ill-formed, incomplete, and
often inconsistent. Access to more granular data available through in-memory technology
makes it possible to drive focused decisions and take actions quickly.
IDC research shows that at the height of the recession, every technology investment
made by SMEs had to have an almost immediate payback. SMEs still need a
compelling financial return on technology investments, but that need is now paired
with another key requirement — the ability to support long-term success. Technology
must be effective, of course, but it also must be compatible with a company's
technology direction and goals moving forward. An increasing number of SMEs are
looking at three- to five-year time horizons when making critical technology
purchasing decisions, including those for BI and analytics technology. This means
that today's technology evaluations should consider BI, analytics, and database
options that are expected to lead the market in the near future. One of these key
technologies is the IMDB, in addition to the applications built on it.
I N- MEMORY DATABASE AS A PLATFORM
FOR A NEW GENERATI ON OF ANALYTI C AND
OPERATI ONAL APPLI CAT I ONS
I n - Me mo r y T e c h n o l o g y D e f i n e d
Disk-based systems require long-running batch jobs for data movement as well as
time and effort to load the data onto disk volumes. But suppose there were no disk
volumes. Suppose the data could be moved at the speed of the processors and
internal network and laid out dynamically in memory for rapid analysis. That is the
idea behind in-memory database systems. This approach greatly accelerates both the
preparation of analytic data and the access to that data.
Because data can be loaded and adjusted in greater volumes and accessed more
quickly with in-memory technology than with disk-based technology, it becomes
possible to manage more data at a more granular level. This results in greater
precision and the ability to drive focused decisions and business actions quickly.
6 #237342 ©2012 IDC
I n - Me mo r y T e c h n o l o g y Ma r k e t O u t l o o k
IMDB is an important dimension of the database management system (DBMS)
landscape and will become more important in the coming years. The shift in
computing economics that makes processors and memory abundant will compel
every DBMS vendor to move in this direction in the future. It is likely that as solid state
memory (SSM) drops in price, main memory will be seen as the primary "home" of a
database, solid state memory will be seen as the overflow area, and disks will be
relegated to recovery functions only. IMDB is becoming regarded as an inevitable
stage in the evolution of database management.
I n - Me mo r y T e c h n o l o g y Ma r k e t D r i v e r s
To be leaders and to compete at the highest level in today's intelligent economy,
organizations of all sizes need to have a platform that enables top performance. One
of the key components of such a platform is in-memory technology.
SAP HANA PLATFORM
The SAP HANA platform is specifically designed to support both operational
applications and analytic applications. It makes possible instant analysis of structured
and unstructured data and the embedding of analytics into operational applications.
The SAP HANA appliance software enables organizations to analyze their business
operations using detailed operational data in real time, while business is happening.
Operational data is captured in memory and made available for instant analysis,
eliminating the typical lag time between when data is captured in business
applications and analysis of that data from reporting systems. It provides insight into
business operations directly from the production database. This in-memory computing
technology combines SAP software with hardware from the company's strategic
hardware partners. Of note is that 16% of SMEs have a data warehouse appliance
and 21% of SMEs are planning to invest in one over the next 12 months.
2
Technology such as SAP HANA represents a completely different way of managing
data warehouse data. Rather than the data being mapped to relational tables stored
on disk, the data is kept in column-wise memory structures. Rather than searching for
data by looking up index entries and using indirect references to find the disk pages
where the data resides, SAP HANA jumps around the memory structure, scanning
columns and following memory pointers, to quickly assemble the desired data. The
result is that queries will run at a significantly faster rate compared with their disk-
based relational database equivalents, yet the process of modeling and reporting data
remains just as straightforward to the user.
U s e C a s e s f o r S ME s wi t h S A P H A N A
In-memory computing technology can be applied to any decision type, in any line of
business, and in any industry. Typical workloads range from operational reporting and
performance management to ad hoc data exploration and dynamic planning.
©2012 IDC #237342 7
In addition to providing functionality for querying and performing n-dimensional analysis
of operational data, SAP HANA includes functionality that can enable unstructured
content analysis, predictive analytics, data exploration, data visualization, and dynamic
planning and forecasting.
SMEs cite planning as the process that would be most improved if relevant planning
applications ran on in-memory computing technology such as SAP HANA. The ability
to iterate through more scenarios within a given time window and change planning
variables and see results in real time is enabled by the processing power of in-
memory computing. Sales, operations, and marketing planning are the top three
business areas in which such benefits will resonate with business users.
3
The top specific applications that would benefit the most from in-memory computing
include financial analytics (planning, consolidation, and close), pricing analytics and
optimization, and customer service analytics.
3
However, as previously mentioned,
most applications across business processes can benefit from the features and
functionality of SAP HANA.
SAP offers several licensing options for the SAP HANA platform. A company might
choose one of the following options, depending on its IT landscape and specific use
cases:
? SAP HANA, Edge edition: For midsize companies looking to accelerate access
to their operational and strategic information assets
? SAP HANA edition for SAP NetWeaver Business Warehouse (SAP NetWeaver
BW): For companies that use SAP NetWeaver BW as their data warehouse
? Limited editions for applications and accelerators: For organizations that are
using SAP HANA with various SAP and partner-built applications
? SAP HANA, Platform edition: Suitable for companies that want a real-time
platform that combines high-volume transactions with analytics to create custom
applications
? SAP HANA, Enterprise edition: Suitable for companies that have larger data
volume challenges
B u s i n e s s a n d I T B e n e f i t s t o U s i n g S A P H A N A
Primary drivers that lead organizations to invest in in-memory technology are
simplicity, cost, performance, and faster access to more granular and complete
information at decision time.
Among SMEs, the most frequently mentioned business benefit of in-memory computing
capabilities is reduction in analysis turnaround time. Other benefits represent a mix of
business process improvements and productivity or efficiency gains. Other frequently
mentioned benefits include reduction in time spent by business staff on data
preparation, cleansing, and aggregation; improved planning accuracy; and an increase
in the frequency of reevaluation of analytic models, plans, and forecasts.
3
8 #237342 ©2012 IDC
Similarly, the IT benefits of in-memory computing can provide important cost savings
and better IT staff allocation. The top two IT benefits are less time spent on creating
data aggregations and less time spent on database administration. Both issues point
to key shortcomings of existing methods of information management and analysis
that require strategies to address performance limitations of disk-based systems.
3
Both business benefits and IT benefits are important. Although IT benefits are more
immediately tangible than business benefits, IT benefits have a limit. For example,
there's only so much you can save by moving database administrators (DBAs) to
technology consolidation or reduction projects and user support rather than storage
tuning. In the end, the business benefits derived from better customer interactions,
more optimized operations, or better, risk-adjusted financial management will
increase organizational value. In many respects, the "cost savings" associated with IT
benefits are limited and can be considered "defense"; that is, let's minimize what we
are spending. In contrast, the improved decision making associated with business
benefits can be considered "offense." These benefits relate to revenue-generating
opportunities, being able to act before a competitor or take advantage of a situation
before circumstances change. In theory, there is no limit to this upside potential.
CHALLENGES AND OPPORTUNI TI ES
The opportunities to employ in-memory technology are not without challenges.
Several potential issues, whether perceived or real, need to be overcome by
organizations looking to deploy in-memory computing technology, including the Edge
edition of SAP HANA. Established IT practices have led potential adopters of in-
memory technology to have common misconceptions about the technology that they
cite as challenges to deployment. They include:
? Cost of the technology itself. Two out of five survey respondents (41%) expect the
cost of the in-memory technology to be a challenge for their organization, making
this the most frequently cited challenge. Higher cost of memory versus disk during
initial deployment needs to be considered in the context of total cost of ownership.
Customers of in-memory technology report needing fewer database administrators,
smaller datacenter footprints, less shelfware, and lower maintenance costs.
Additionally, the downstream business benefits of using in-memory technology need
to be taken into account when evaluating ROI. This is especially critical for SMEs,
which are invariably constrained by both IT budgets and IT staff.
? Multisource and multistructured data integration. The next most frequently
cited challenges, after the cost of the technology itself, are integration of data
from various sources and integration of data of various types. Integration of data
from various sources has always been a challenge using traditional data
warehousing techniques. While IMDB doesn't make this problem disappear, it
can make it easier to relate more data with fewer aggregations requiring up-front
planning in anticipation of the queries users might pose. This efficiency gain in
the data integration and preparation process is critical for SMEs that need to
optimally leverage their limited human IT resources. Rather than spending time
building data cubes, staff can focus on higher value-added tasks.
©2012 IDC #237342 9
? Scalability to handle large data sets and Big Data use cases. There is no
requirement to have very large data sets in order to benefit from in-memory
computing. In fact, most uses for IMDBs today don't involve petabytes of data,
and 60% of the overall IT and business managers of SMEs are not even aware
of the term Big Data. Nevertheless, IMDBs can handle relatively large data sets if
enough memory is allocated for the overall solution, which may involve servers
with shared memory pools.
1
? User access and security management. Most IT managers would expect an
enterprise-ready system to manage user access and security with de facto
industry-standard integrations, and IMDB technologies support this functionality.
However, our research revealed that real-time access to data could lead to
misuse. Someone could run a report at a point in time and that data would vary
from someone running the same report a few minutes later, leading to different
conclusions. There is some loss of control when information is made widely
available, but it is an issue of policy and user education, not a technology
shortcoming. IT will need to delineate the difference between real-time analysis
and time-stamped, compliant production or operational reports. Taking on this
consultative and training role may be outside the comfort zone of many SME IT
groups, yet it provides additional value and can underscore IT's strategic role to
the rest of the organization, especially senior management.
? Backup, recovery, and availability. A common misconception regarding IMDB is
that it lacks the atomicity, consistency, isolation, and durability (ACID) properties of
a transactional database. This is not true. Most IMDB implementations used for
transaction processing still have transaction logs for error recovery and can stream
the logs to physically persistent storage. They also commonly replicate their
memory contents to other servers to provide high-availability functionality through
failover support.
? Existing investments. IT has built data warehouses and data marts across the
organization, and they cost money and time. Building around, or in support of,
these existing investments to take advantage of real-time access or rapid
analysis where a business process could benefit from it will enable those
investments to be valuable data sources, retain their current purpose, and be
enhanced by IMDB where needed. This opportunity to complement existing
technology with new technology is especially important for SMEs that may not be
able to afford to have parallel teams supporting two or more technologies for a
similar use case. An incremental approach will be especially appealing to SMEs
looking for lower-risk options by enhancing existing solutions.
10 #237342 ©2012 IDC
RECOMMENDATI ONS
The first recommendation for any organization, regardless of its size, is to develop a
BI and analytics strategy that encompasses evaluations of decision-making
processes; decision makers' needs; and data, technology, and staffing requirements.
The lack of such a strategy is especially apparent in the SME segment of the market,
where only 20% of organizations have a stated business analytics strategy.
1
More operational recommendations for both business managers and IT managers are
discussed in this section.
R e c o mme n d a t i o n s f o r B u s i n e s s Ma n a g e r s
SAP HANA can be applied to solve many business problems. When weighing
whether the technology is appropriate for improving specific business processes,
consider the following:
? Identify decision-making processes and decision makers and question whether
they are supported by relevant, timely information. Often, a service level could be
maintained at lower risk or cost or improved for competitive differentiation if
analysis related to decisions impacting that service level is performed faster or
with better accuracy. Adding an IMDB technology at this decision point is more
likely to lead to business improvements.
? Examine where real-time data access is a necessity but not available today. If
the barrier is technology related, then an IMDB technology is applicable. Real-
time access to data can improve the speed and accuracy of decision making,
which, in turn, can enable improved business processes for addressing customer
needs in real time or managing supplier relationships in real time. In addition,
access to real-time data can help uncover ways of innovating a process, a
product, or a service that was not feasible before. Both of these benefits have
significant potential to improve SME operations.
? Examine a process where people perform analysis less frequently than actual
changes within a process occur and IMDB can solve this problem. For example,
inventory management is often done based on latent aggregation of supply and
demand data. However, when decisions can be made based on actual inventory
flows during a day, then there could be reductions in out-of-stock events or early
warnings of supplier performance degradation.
R e c o mme n d a t i o n s f o r I T Ma n a g e r s
The emergence of in-memory DBMS as a dominant form will not happen all at once.
IT managers should consider how they might evolve their IT systems in such a way
as to exploit IMDB technology both now and in the future. The SAP HANA platform's
current columnar approach is well suited to the analytic workload, and as SAP HANA
evolves, it will also support operational workloads.
? Not all data is created equal. Some data is seldom accessed and may be
maintained on disk because it is nonvolatile and disk is cheap. Some data is
accessed a bit more frequently and may be kept in solid state memory (also
©2012 IDC #237342 11
called flash memory). Dynamic, online data will increasingly need to be held in
memory all the time. IT managers should consider how much of each they have
— and are likely to have going forward — and plan accordingly.
? Business issues can arise suddenly, requirements can change quickly, and a
system that requires a batch unload from a disk-based database, followed by
construction of a disk-based cube or loading of a disk-based data mart, requires
a lot of time. Consider in-memory DBMS as a tool that will enable decision
makers to respond to business changes in real time.
? The new economics of computing, which derive from large memory models, 64-
bit addressability, fast processors, and cheap memory, make it possible to design
databases that are far faster and more scalable than was possible when the only
option was to base data management on spinning disks. Consider in-memory
DBMS technology as a means to reduce your company's operational IT costs
associated with storage.
? A fundamental barrier to scalability for a disk-based database is the bottleneck
represented by the storage system. DBAs spend an enormous amount of their
time rebuilding indexes, unloading and reloading data, and reallocating data
across storage volumes to minimize I/O time. Many SMEs may not have the
expert DBAs to perform these tasks, or if they do have expert DBAs, these tasks
result in a backlog of more high-value tasks that DBAs could be performing.
CONCLUSI ON
In-memory database technology has emerged as a key means of boosting performance
and scalability and containing storage costs. This technology has evolved from use only
for caching, or for extremely high-speed data systems, to much more mainstream IT
applications. Today, most systems have multiple processors and multiple cores per
processor. Enterprise servers typically use 64-bit memory addressing and are stocked
with multiple gigabytes of main memory. This means that the economics of computing
have swung in favor of in-memory databases for many workloads.
Today's reality for most SMEs is represented by data that is increasing in volume and
complexity. Business competitiveness requires the ability to access this data at a
granular level and on a very timely basis. Increasingly, business users at SMEs
require self-service BI and analytics functionality that gives them access to this
granular and timely data through their preferred data visualization and reporting tools.
For SMEs, the "how" of information delivery can be just as important as the "what" of
information delivery.
In-memory computing is essential to meeting both requirements, and SAP HANA is a
clear example of that technology at work today. It not only provides an in-memory
data processing engine but also serves as a platform for integration with end user–
facing BI tools, such as SAP BusinessObjects Visual Intelligence software and SAP
BusinessObjects Explorer software. Consider the data management and analysis
platform as well as the BI and analytics tools that it supports when making a
technology selection.
12 #237342 ©2012 IDC
SOURCES
1. IDC's Vertical IT and Communications Survey, May 2012 (n = 1,062 SMEs)
2. IDC and Computerworld Business Intelligence and Analytics Survey, February
2012 (n = 82 SMEs)
3. IDC's SAP HANA Edge Market Assessment, August 2011 (n = 282 SMEs)
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approval from the appropriate IDC Vice President or Country Manager. A draft of the
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deny approval of external usage for any reason.
Copyright 2012 IDC. Reproduction without written permission is completely forbidden.
doc_402620955.pdf
How Small and Midsize Enterprises Can Sharpen Performance with Next Generation Business Intelligence and Analytics
WHI TE PAPER
How Smal l a nd Mi ds i z e Ent er pr i ses Ca n Shar pe n
Per f or ma nc e wi t h Ne x t - Ge ne r a t i on Bus i ness I nt e l l i gence
a nd Ana l yt i c s
Sponsored by: SAP
Dan Vesset Raymond Boggs
October 2012
EXECUTI VE SUMMARY
Small and midsize enterprises (SMEs), which IDC defines as having fewer than 1,000
employees, have been especially challenged by the changing world economy, new
competitive pressures, and the increasing pace of business in general. As the
digitization of a growing number of business processes continues, many SMEs are
finding a growing need to leverage customer, operational, and financial data for better
decision making. Unlike large enterprises, which have extensive technology and other
resources to draw on, SMEs are limited in the extent to which they can leverage the
latest technology to measure current performance and uncover new insights to help
improve interactions with customers or suppliers, to introduce new products or
services, and to optimize operations. The latest generation of in-memory database
(IMDB) technology — such as the SAP HANA platform — and applications deployed
on it are providing SMEs with effective capabilities with attractive return on investment
(ROI) and total cost of ownership that will improve business decision making,
competitive positioning, and long-term business success.
For SMEs, there may be a sense that management tools are already satisfactory for
running the business. Regular reporting mechanisms have worked in the past, and
formal planning for the future is often considered an exercise in extending the trend
lines from recent quarters. In truth, though, the capabilities that firms used in the past
are simply inadequate for today's fast-moving business environment. Relying on
monthly or quarterly sales results to gauge business success and develop plans is
like driving down a dark highway using just a rearview mirror. The approach is far
more risky than using headlights to judge the shifting conditions of the road ahead.
Real-time results, provided through business intelligence (BI) and analytics
technology, can provide management with the kind of information needed to evaluate
business health (descriptive) but also judge the value of potential alternative courses
of action (predictive). The latter is far more important in the long term and is
associated with the two critical attributes of the most successful companies: agility
and flexibility. While the investment in business intelligence resources should be
justified on the basis of performance improvements, the real value will be far greater:
identifying new business opportunities that will enhance a company's long-term
growth prospects. In effect, IT management should make the case for investment
based on the tangible financial benefits that can be achieved in the short term, but
general management should appreciate (and be excited by) the windows to new
opportunities that effective BI and analytics will open.
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The sections of this IDC white paper are organized around key topics to pave the way
for an effective implementation of a new generation of BI and analytics solutions:
? Business Analytics Best Practices: What can we learn from others?
? Business Analytics Requirements and Pain Points: What are the "must have"
capabilities and the "must avoid" pitfalls in implementation?
? In-Memory Database as a Platform for a New Generation of Analytic and
Operational Applications: How is new technology making a difference?
? SAP HANA Platform: SAP in-memory computing technology use case with a
discussion of both business benefits and IT benefits.
? Challenges and Opportunities: A list of categories that you will need to be aware
of and potentially address.
? Recommendations: Business managers and IT managers will have different
concerns, and you should make sure you understand the position of others.
? Conclusion: Information delivery can be a challenge for organizations because of
the changing nature of the data, but their ability to address this challenge will be
increasingly important for business success.
BUSI NESS ANALYTI CS BEST PRACTI CES
In today's global economy, success in the form of better performance is increasingly
defined by having the freedom to innovate, to provide customers with better products
and services, and to act faster and with greater insight within ever-shorter decision
windows in the face of uncertainty within a rapidly evolving economic system.
There is growing quantifiable evidence that organizations with higher business
analytics competency outperform their less analytically oriented peers. IDC research
shows that most analytically oriented organizations are 20% more likely to be among
the most competitive organizations within their industry.
Today, access to information, combined with the ability to analyze and act upon that
information, creates competitive advantage in commercial transactions, enables
sustainable management of communities, and promotes appropriate distribution of
social, healthcare, and educational services.
The information access, analysis, and management challenges of the intelligent
economy can overwhelm SMEs that are unprepared for the emerging changes. While
many will manage through the process, they will find things far more challenging than
SMEs that anticipate and plan for their changing information needs. IDC defines the
former group of reactive organizations as "fumblers" and the latter group as "fact
finders." As described in IDC's study Analytical Orientation and Competitiveness: The
Difference Between Fact Finders and Fumblers (IDC #223408, May 2010), "fact
finders" are organizations that have the highest levels of the following characteristics:
©2012 IDC #237342 3
? Reliance on analytics, which is defined as the degree to which the manager
relies on analytics (as opposed to experience or intuition) for decision making
? Influence on actions, which is defined as the extent to which the output of the
organization's business analytics solutions influences all employees' actions
? Criticality to competitiveness, which is defined as the perceived level of
criticality of the business analytics solutions to the organization's competitiveness
? Effectiveness of analysis on decision making, which is defined as the
importance of the organization's business analytics technology and processes in
helping improve individual decision making or in facilitating intragroup or
intergroup decision making
Our research demonstrates that, as a group, fact finders are more competitive within
their industries (see Figure 1).
F I GURE 1
An al y t i c a l Or i en t at i o n o f L e a d e r s Ver s u s L a gg a r d s
Source: IDC, 2012
80% of leaders (most competitive organizations in their industry) are fact finders
(have a higher level of analytical orientation), while only 58% of laggards (least
competitive organizations) are fact finders (see Figure 2). In other words,
organizations that are more competitive within their industries have higher levels of
analytical orientation.
While being a fact finder does not ensure success, competitive differentiation —
based on the application of analytics for ad hoc analysis, discovery, or planning
processes and embedded into other business applications — will continue to make a
difference for many SMEs.
Fact Finders
Fact Finders
Fumblers
Fumblers
0% 20% 40% 60% 80% 100%
Leaders
Laggards
(% of respondents)
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BUSI NESS ANALYTI CS REQUI REMENTS AND
PAI N POI NTS
Executives, managers, and other decision makers at SMEs want the most relevant,
timely, and accurate information to enable better decision making. Over 40% of SMEs
plan to make BI and analytics technology available to more executives as well as
power users, including managers and analysts.
SMEs want the right tools that will provide this information to them. Forty percent of SMEs
rank BI and analytics as a high or very high priority investment for their organizations.
Additionally, more SMEs increasingly consider BI and analytics tools mission critical. Sixty
percent of SMEs state that if their BI and analytics solution were out of service by up to
one day, it would have a material negative impact on business operations.
1
Yet, adoption of BI, analytics, and data warehousing technology among SMEs is relatively
low. Only 10% of SMEs state that there is widespread reliance on BI and analytics on a
daily or ongoing basis.
2
Only 13% say they have a relational data warehouse today.
1
What is keeping SMEs from embracing the latest tools? From one recent IDC survey, the
top three areas that SMEs would most like to see improved in their BI and analytics
solutions are flexibility in accessing, analyzing, and manipulating data; intuitiveness of the
user interface; and frequency of data updates.
1
From another survey, the top three areas
that SMEs would most like to see improved in their BI and analytics solutions are data
visualization, ability to do scenario evaluation or what-if analysis, and generally faster
response time to queries.
2
In each case, the message is clear — users want more
flexibility, self-service, and real-time access to information. Having increasingly become
accustomed to real-time access to relevant information in their personal lives, employees
expect the same in their workplaces. Decision makers at SMEs expect to have access to
information at decision time, which may mean access via a mobile device or embedded in
operational applications. Speedy decision making based on real-time information
presented in a clear and compelling way can help drive company success.
Yet, self-service capabilities for BI and analytics users at SMEs lag behind those of large
enterprises, and 20% of SMEs provide no self-service functionality to their business users.
It is a reasonable assumption that this stems from substandard system performance,
which requires IT to keep full control of the technology and to focus on prebuilding rigid
user interfaces and data models, which, in turn, have lengthy internal development cycles,
to address any new user requirements.
2
Only a quarter of SMEs agree that the speed of
their IT department's response to BI and analytics requests meets end-user expectations.
3
SMEs, like their larger counterparts, increasingly need to deal with a broader set of
data sources and types. The spectrum of data that SMEs report capturing besides
transactional data includes text from non–social networking sources (e.g., email,
forms, surveys), chatter from social networks, GIS data, Web logs, machine-
generated data from sensors, audio, and video. While some data types, especially
audio and video, require highly specialized transformation software to make the data
usable by analytic tools, it is increasingly a requirement for business analytics
solutions to be able to integrate data of multiple types and structures. Data integration
is the second most frequently cited BI and analytics challenge for SMEs, trailing only
the cost of the technology.
©2012 IDC #237342 5
IT tools and their functionality are a key part of the issue, but so is staffing. Most
SMEs do not have the dedicated experts in business analytics software to design and
develop a data warehouse, data marts, multidimensional cubes, and a variety of end-
user interfaces ranging from reports and dashboards to business process and
industry-specific analytic applications. Insufficient specialized IT skills are the third
most frequently cited BI and analytics challenge among SMEs.
1
Often, business analysis and decision making are done using managed data
structures such as data marts or analytic cubes, which, in turn, are fed from data in an
enterprise data warehouse or operational data sources of various kinds. Building or
refreshing these structures takes time and staff resources and usually must be
scheduled in advance. The problem is that business issues can arise suddenly and
requirements can change quickly, and a system too slow to react to business
changes can derail the achievement of business goals.
Many managers and analysts resort to getting subsets of data in one way or another and
often build their own spreadsheets rather than rely on IT to build the structures they need.
As a result, they sometimes base key decisions on data that is ill-formed, incomplete, and
often inconsistent. Access to more granular data available through in-memory technology
makes it possible to drive focused decisions and take actions quickly.
IDC research shows that at the height of the recession, every technology investment
made by SMEs had to have an almost immediate payback. SMEs still need a
compelling financial return on technology investments, but that need is now paired
with another key requirement — the ability to support long-term success. Technology
must be effective, of course, but it also must be compatible with a company's
technology direction and goals moving forward. An increasing number of SMEs are
looking at three- to five-year time horizons when making critical technology
purchasing decisions, including those for BI and analytics technology. This means
that today's technology evaluations should consider BI, analytics, and database
options that are expected to lead the market in the near future. One of these key
technologies is the IMDB, in addition to the applications built on it.
I N- MEMORY DATABASE AS A PLATFORM
FOR A NEW GENERATI ON OF ANALYTI C AND
OPERATI ONAL APPLI CAT I ONS
I n - Me mo r y T e c h n o l o g y D e f i n e d
Disk-based systems require long-running batch jobs for data movement as well as
time and effort to load the data onto disk volumes. But suppose there were no disk
volumes. Suppose the data could be moved at the speed of the processors and
internal network and laid out dynamically in memory for rapid analysis. That is the
idea behind in-memory database systems. This approach greatly accelerates both the
preparation of analytic data and the access to that data.
Because data can be loaded and adjusted in greater volumes and accessed more
quickly with in-memory technology than with disk-based technology, it becomes
possible to manage more data at a more granular level. This results in greater
precision and the ability to drive focused decisions and business actions quickly.
6 #237342 ©2012 IDC
I n - Me mo r y T e c h n o l o g y Ma r k e t O u t l o o k
IMDB is an important dimension of the database management system (DBMS)
landscape and will become more important in the coming years. The shift in
computing economics that makes processors and memory abundant will compel
every DBMS vendor to move in this direction in the future. It is likely that as solid state
memory (SSM) drops in price, main memory will be seen as the primary "home" of a
database, solid state memory will be seen as the overflow area, and disks will be
relegated to recovery functions only. IMDB is becoming regarded as an inevitable
stage in the evolution of database management.
I n - Me mo r y T e c h n o l o g y Ma r k e t D r i v e r s
To be leaders and to compete at the highest level in today's intelligent economy,
organizations of all sizes need to have a platform that enables top performance. One
of the key components of such a platform is in-memory technology.
SAP HANA PLATFORM
The SAP HANA platform is specifically designed to support both operational
applications and analytic applications. It makes possible instant analysis of structured
and unstructured data and the embedding of analytics into operational applications.
The SAP HANA appliance software enables organizations to analyze their business
operations using detailed operational data in real time, while business is happening.
Operational data is captured in memory and made available for instant analysis,
eliminating the typical lag time between when data is captured in business
applications and analysis of that data from reporting systems. It provides insight into
business operations directly from the production database. This in-memory computing
technology combines SAP software with hardware from the company's strategic
hardware partners. Of note is that 16% of SMEs have a data warehouse appliance
and 21% of SMEs are planning to invest in one over the next 12 months.
2
Technology such as SAP HANA represents a completely different way of managing
data warehouse data. Rather than the data being mapped to relational tables stored
on disk, the data is kept in column-wise memory structures. Rather than searching for
data by looking up index entries and using indirect references to find the disk pages
where the data resides, SAP HANA jumps around the memory structure, scanning
columns and following memory pointers, to quickly assemble the desired data. The
result is that queries will run at a significantly faster rate compared with their disk-
based relational database equivalents, yet the process of modeling and reporting data
remains just as straightforward to the user.
U s e C a s e s f o r S ME s wi t h S A P H A N A
In-memory computing technology can be applied to any decision type, in any line of
business, and in any industry. Typical workloads range from operational reporting and
performance management to ad hoc data exploration and dynamic planning.
©2012 IDC #237342 7
In addition to providing functionality for querying and performing n-dimensional analysis
of operational data, SAP HANA includes functionality that can enable unstructured
content analysis, predictive analytics, data exploration, data visualization, and dynamic
planning and forecasting.
SMEs cite planning as the process that would be most improved if relevant planning
applications ran on in-memory computing technology such as SAP HANA. The ability
to iterate through more scenarios within a given time window and change planning
variables and see results in real time is enabled by the processing power of in-
memory computing. Sales, operations, and marketing planning are the top three
business areas in which such benefits will resonate with business users.
3
The top specific applications that would benefit the most from in-memory computing
include financial analytics (planning, consolidation, and close), pricing analytics and
optimization, and customer service analytics.
3
However, as previously mentioned,
most applications across business processes can benefit from the features and
functionality of SAP HANA.
SAP offers several licensing options for the SAP HANA platform. A company might
choose one of the following options, depending on its IT landscape and specific use
cases:
? SAP HANA, Edge edition: For midsize companies looking to accelerate access
to their operational and strategic information assets
? SAP HANA edition for SAP NetWeaver Business Warehouse (SAP NetWeaver
BW): For companies that use SAP NetWeaver BW as their data warehouse
? Limited editions for applications and accelerators: For organizations that are
using SAP HANA with various SAP and partner-built applications
? SAP HANA, Platform edition: Suitable for companies that want a real-time
platform that combines high-volume transactions with analytics to create custom
applications
? SAP HANA, Enterprise edition: Suitable for companies that have larger data
volume challenges
B u s i n e s s a n d I T B e n e f i t s t o U s i n g S A P H A N A
Primary drivers that lead organizations to invest in in-memory technology are
simplicity, cost, performance, and faster access to more granular and complete
information at decision time.
Among SMEs, the most frequently mentioned business benefit of in-memory computing
capabilities is reduction in analysis turnaround time. Other benefits represent a mix of
business process improvements and productivity or efficiency gains. Other frequently
mentioned benefits include reduction in time spent by business staff on data
preparation, cleansing, and aggregation; improved planning accuracy; and an increase
in the frequency of reevaluation of analytic models, plans, and forecasts.
3
8 #237342 ©2012 IDC
Similarly, the IT benefits of in-memory computing can provide important cost savings
and better IT staff allocation. The top two IT benefits are less time spent on creating
data aggregations and less time spent on database administration. Both issues point
to key shortcomings of existing methods of information management and analysis
that require strategies to address performance limitations of disk-based systems.
3
Both business benefits and IT benefits are important. Although IT benefits are more
immediately tangible than business benefits, IT benefits have a limit. For example,
there's only so much you can save by moving database administrators (DBAs) to
technology consolidation or reduction projects and user support rather than storage
tuning. In the end, the business benefits derived from better customer interactions,
more optimized operations, or better, risk-adjusted financial management will
increase organizational value. In many respects, the "cost savings" associated with IT
benefits are limited and can be considered "defense"; that is, let's minimize what we
are spending. In contrast, the improved decision making associated with business
benefits can be considered "offense." These benefits relate to revenue-generating
opportunities, being able to act before a competitor or take advantage of a situation
before circumstances change. In theory, there is no limit to this upside potential.
CHALLENGES AND OPPORTUNI TI ES
The opportunities to employ in-memory technology are not without challenges.
Several potential issues, whether perceived or real, need to be overcome by
organizations looking to deploy in-memory computing technology, including the Edge
edition of SAP HANA. Established IT practices have led potential adopters of in-
memory technology to have common misconceptions about the technology that they
cite as challenges to deployment. They include:
? Cost of the technology itself. Two out of five survey respondents (41%) expect the
cost of the in-memory technology to be a challenge for their organization, making
this the most frequently cited challenge. Higher cost of memory versus disk during
initial deployment needs to be considered in the context of total cost of ownership.
Customers of in-memory technology report needing fewer database administrators,
smaller datacenter footprints, less shelfware, and lower maintenance costs.
Additionally, the downstream business benefits of using in-memory technology need
to be taken into account when evaluating ROI. This is especially critical for SMEs,
which are invariably constrained by both IT budgets and IT staff.
? Multisource and multistructured data integration. The next most frequently
cited challenges, after the cost of the technology itself, are integration of data
from various sources and integration of data of various types. Integration of data
from various sources has always been a challenge using traditional data
warehousing techniques. While IMDB doesn't make this problem disappear, it
can make it easier to relate more data with fewer aggregations requiring up-front
planning in anticipation of the queries users might pose. This efficiency gain in
the data integration and preparation process is critical for SMEs that need to
optimally leverage their limited human IT resources. Rather than spending time
building data cubes, staff can focus on higher value-added tasks.
©2012 IDC #237342 9
? Scalability to handle large data sets and Big Data use cases. There is no
requirement to have very large data sets in order to benefit from in-memory
computing. In fact, most uses for IMDBs today don't involve petabytes of data,
and 60% of the overall IT and business managers of SMEs are not even aware
of the term Big Data. Nevertheless, IMDBs can handle relatively large data sets if
enough memory is allocated for the overall solution, which may involve servers
with shared memory pools.
1
? User access and security management. Most IT managers would expect an
enterprise-ready system to manage user access and security with de facto
industry-standard integrations, and IMDB technologies support this functionality.
However, our research revealed that real-time access to data could lead to
misuse. Someone could run a report at a point in time and that data would vary
from someone running the same report a few minutes later, leading to different
conclusions. There is some loss of control when information is made widely
available, but it is an issue of policy and user education, not a technology
shortcoming. IT will need to delineate the difference between real-time analysis
and time-stamped, compliant production or operational reports. Taking on this
consultative and training role may be outside the comfort zone of many SME IT
groups, yet it provides additional value and can underscore IT's strategic role to
the rest of the organization, especially senior management.
? Backup, recovery, and availability. A common misconception regarding IMDB is
that it lacks the atomicity, consistency, isolation, and durability (ACID) properties of
a transactional database. This is not true. Most IMDB implementations used for
transaction processing still have transaction logs for error recovery and can stream
the logs to physically persistent storage. They also commonly replicate their
memory contents to other servers to provide high-availability functionality through
failover support.
? Existing investments. IT has built data warehouses and data marts across the
organization, and they cost money and time. Building around, or in support of,
these existing investments to take advantage of real-time access or rapid
analysis where a business process could benefit from it will enable those
investments to be valuable data sources, retain their current purpose, and be
enhanced by IMDB where needed. This opportunity to complement existing
technology with new technology is especially important for SMEs that may not be
able to afford to have parallel teams supporting two or more technologies for a
similar use case. An incremental approach will be especially appealing to SMEs
looking for lower-risk options by enhancing existing solutions.
10 #237342 ©2012 IDC
RECOMMENDATI ONS
The first recommendation for any organization, regardless of its size, is to develop a
BI and analytics strategy that encompasses evaluations of decision-making
processes; decision makers' needs; and data, technology, and staffing requirements.
The lack of such a strategy is especially apparent in the SME segment of the market,
where only 20% of organizations have a stated business analytics strategy.
1
More operational recommendations for both business managers and IT managers are
discussed in this section.
R e c o mme n d a t i o n s f o r B u s i n e s s Ma n a g e r s
SAP HANA can be applied to solve many business problems. When weighing
whether the technology is appropriate for improving specific business processes,
consider the following:
? Identify decision-making processes and decision makers and question whether
they are supported by relevant, timely information. Often, a service level could be
maintained at lower risk or cost or improved for competitive differentiation if
analysis related to decisions impacting that service level is performed faster or
with better accuracy. Adding an IMDB technology at this decision point is more
likely to lead to business improvements.
? Examine where real-time data access is a necessity but not available today. If
the barrier is technology related, then an IMDB technology is applicable. Real-
time access to data can improve the speed and accuracy of decision making,
which, in turn, can enable improved business processes for addressing customer
needs in real time or managing supplier relationships in real time. In addition,
access to real-time data can help uncover ways of innovating a process, a
product, or a service that was not feasible before. Both of these benefits have
significant potential to improve SME operations.
? Examine a process where people perform analysis less frequently than actual
changes within a process occur and IMDB can solve this problem. For example,
inventory management is often done based on latent aggregation of supply and
demand data. However, when decisions can be made based on actual inventory
flows during a day, then there could be reductions in out-of-stock events or early
warnings of supplier performance degradation.
R e c o mme n d a t i o n s f o r I T Ma n a g e r s
The emergence of in-memory DBMS as a dominant form will not happen all at once.
IT managers should consider how they might evolve their IT systems in such a way
as to exploit IMDB technology both now and in the future. The SAP HANA platform's
current columnar approach is well suited to the analytic workload, and as SAP HANA
evolves, it will also support operational workloads.
? Not all data is created equal. Some data is seldom accessed and may be
maintained on disk because it is nonvolatile and disk is cheap. Some data is
accessed a bit more frequently and may be kept in solid state memory (also
©2012 IDC #237342 11
called flash memory). Dynamic, online data will increasingly need to be held in
memory all the time. IT managers should consider how much of each they have
— and are likely to have going forward — and plan accordingly.
? Business issues can arise suddenly, requirements can change quickly, and a
system that requires a batch unload from a disk-based database, followed by
construction of a disk-based cube or loading of a disk-based data mart, requires
a lot of time. Consider in-memory DBMS as a tool that will enable decision
makers to respond to business changes in real time.
? The new economics of computing, which derive from large memory models, 64-
bit addressability, fast processors, and cheap memory, make it possible to design
databases that are far faster and more scalable than was possible when the only
option was to base data management on spinning disks. Consider in-memory
DBMS technology as a means to reduce your company's operational IT costs
associated with storage.
? A fundamental barrier to scalability for a disk-based database is the bottleneck
represented by the storage system. DBAs spend an enormous amount of their
time rebuilding indexes, unloading and reloading data, and reallocating data
across storage volumes to minimize I/O time. Many SMEs may not have the
expert DBAs to perform these tasks, or if they do have expert DBAs, these tasks
result in a backlog of more high-value tasks that DBAs could be performing.
CONCLUSI ON
In-memory database technology has emerged as a key means of boosting performance
and scalability and containing storage costs. This technology has evolved from use only
for caching, or for extremely high-speed data systems, to much more mainstream IT
applications. Today, most systems have multiple processors and multiple cores per
processor. Enterprise servers typically use 64-bit memory addressing and are stocked
with multiple gigabytes of main memory. This means that the economics of computing
have swung in favor of in-memory databases for many workloads.
Today's reality for most SMEs is represented by data that is increasing in volume and
complexity. Business competitiveness requires the ability to access this data at a
granular level and on a very timely basis. Increasingly, business users at SMEs
require self-service BI and analytics functionality that gives them access to this
granular and timely data through their preferred data visualization and reporting tools.
For SMEs, the "how" of information delivery can be just as important as the "what" of
information delivery.
In-memory computing is essential to meeting both requirements, and SAP HANA is a
clear example of that technology at work today. It not only provides an in-memory
data processing engine but also serves as a platform for integration with end user–
facing BI tools, such as SAP BusinessObjects Visual Intelligence software and SAP
BusinessObjects Explorer software. Consider the data management and analysis
platform as well as the BI and analytics tools that it supports when making a
technology selection.
12 #237342 ©2012 IDC
SOURCES
1. IDC's Vertical IT and Communications Survey, May 2012 (n = 1,062 SMEs)
2. IDC and Computerworld Business Intelligence and Analytics Survey, February
2012 (n = 82 SMEs)
3. IDC's SAP HANA Edge Market Assessment, August 2011 (n = 282 SMEs)
C o p y r i g h t N o t i c e
External Publication of IDC Information and Data — Any IDC information that is to be
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approval from the appropriate IDC Vice President or Country Manager. A draft of the
proposed document should accompany any such request. IDC reserves the right to
deny approval of external usage for any reason.
Copyright 2012 IDC. Reproduction without written permission is completely forbidden.
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