Every company, regardless of industry, wrestles with the same questions about their data and business information: What is important and what is just noise? How do I obtain, store, and retrieve the information I need to support the decision processes in my organization? How often must my information be updated to be useful? Sometimes the question is as simple as: How do I know I'm looking at the most current report?
Though analytics for standard business processes
in finance or HR are helpful, companies are seeking
insight into the particular needs of their respective
business. Within SAP's industry-specific solutions
lies analytic functionality designed to address exactly
these business information needs. To see the level
of granularity that SAP provides, let's take the
example of a specific industry: consumer products
(CP). These are companies known to every consumer:
Procter & Gamble, Nestlé, Unilever,
Kraft Foods, Nike. While these companies ask themselves
the questions listed above, they also face numerous
challenges that are unique to their line of business.
How do you compete more effectively in an industry:
- That introduces more than 35,000 new items each
year — the vast majority of which fail?
- Where manufacturers carry an average of 47
days of inventory — costing a lot of money?
- Where customer order fulfillment is only 70
percent — risking the business relationship
and consumer satisfaction and loyalty?
- Where only 16 percent of a manufacturer's trade promotions turn a profit?
- That has retail out-of-stock rates between
6 and 12 percent — and
that often reach 20 percent during promotions — risking
the consumer's loyalty to your brands and products?
To address globalization, shifting markets, fickle consumer behavior, changing business models, and mergers and acquisitions, CP companies digest terabytes of information of divergent quantity and quality. This information pours into the company using different data structures, languages, and dialects. The same product may have ten different codes and a single consumer five different identities.
While the challenges found in the CP industry are
unique, the process one follows to address those
challenges — and the tools SAP makes available — have
counterparts in other industries. The lessons learned
here can be transferred to the more than 25 industries
SAP serves. At the end of this article, we'll also
present a technology roadmap that any company can
use to take advantage of analytics in their respective
A New Approach to Improve Decision-Making Capabilities
SAP serves more than 3,200 customers within the consumer products industry and has translated that
deep insight of CP industry trends, decision-making processes, and business-critical analyses into business solutions and an overall architecture that represents a solid
foundation for providing the right information, at the right time, to the right people, at the right quality.
The architecture for generating analytics useful to the consumer products industry is no different than for any other business. In general we employ a four-layer model for all analytical solutions (see Figure 1). These
layers need to be connected in order to deliver perfect alignment for all users' decision making.
To understand how this approach to analytics translates on an industry-specific level, let's take our CP example one step further with a look at Trade Promotion Management.
|Four-Layer, Cross-Industry Architecture Model for Analytics
Example: Trade Promotion Management
Trade Promotion Management (TPM) is the subprocess
within the consumer products industry that connects
the overall marketing strategy with specific customer
promotion tactics such as features, displays, and
temporarily reduced prices — for example, "Buy
four, get five" or "Purchase a promoted product and
get an additional product free."
Consumer products companies spend up to 25 percent of their sales revenue on trade promotions and campaigns. Thousands of promotions run at any given moment, but many CP companies have difficulty differentiating between those promotions that are profitable and those that are not. These companies know they have to promote their products, but more because "everyone does it" rather than because of any serious analysis or decision making in advance. In too many instances, trade promotion spending has become a cost of doing business,
as opposed to an opportunity to drive incremental brand volume and profit.
The opportunities for analytics to assist in the TPM process speak directly to a CP company's bottom line. If a typical CP company with annual sales of $5 billion recognizes a savings of just 2 percent of TPM costs, it could result in an additional $25 million operating profit.
Asking the Right Questions
Consider an account manager responsible for trade promotion management in a consumer products company. How can that manager get the right information at the right time to make optimal decisions?
An account manager might ask:
- Which displays, features, and reduced-price promotions for which products and brands were successful, returning the highest profit or sales growth? Which worked better based on a combination of tactics? Why? What can we learn and apply to future promotions?
- Do we have an adequate budget with the appropriate flexibility to be able
to respond to changing conditions mid-promotion? Can we curtail inefficient promotions and extend profitable ones?
- When planning and executing dozens, if not hundreds, of promotions, can we quickly identify the top ten or bottom ten instead of having to review
and monitor all of them?
SAP provides a variety of analytics — and
ways to present them — that can generate the
answers to these industry-specific business questions.
The additional challenge is to select the most appropriate
and efficient means of presentation. For decision
makers, SAP Analytics applications are particularly
suited for quick, at-a-glance insight and understanding
about what action should be taken (see sidebar below
for more on analytic application design).
5-Step Implementation Roadmap to Enhance Business Effectiveness
For a successful analytics implementation, we need more than an effective analytic application. It is equally important to have the right data at the right moment from the right sources. Making decisions based on analytics must replace business decision making based on a "gut feeling." To accomplish this, you must have the intelligent infrastructure in place that will enable you to connect the dots between your corporate strategy, actual data, and business forecasts.
We recommend that you rethink your architecture along the lines described as follows to create the best environment for getting the most out of your analytics. We offer this five-step process to reach that goal (see Figure 2). Once again we will use the example of our account manager, but this approach will work for any analytics implementation, regardless
of industry or role.
|Five-Step Roadmap to Predictive Forecasting for Trade Promotions
1. mySAP ERP: The Enabler of Process Harmonization
Our roadmap begins with an overall harmonization of business processes, which requires moving to the
mySAP Enterprise Resource Planning (mySAP ERP) system on the SAP NetWeaver platform. This transition
will not only allow efficient business process management, but will also ensure that all the
appropriate internal data points are being captured for future decision making.
Once mySAP ERP is in place, our account manager, for example, will now be able to take advantage
of the sales and execution processes, especially within the order-to-cash cycle.
2. SAP BW and MDM: Data Synchronization and Basic Account Analysis
Different sources and data models, especially within a collaborative world, require a
standardization and harmonization of master data and operational data, something that becomes
even more difficult with each new merger and acquisition.
At this crucial point, SAP NetWeaver Master Data Management (MDM) with global data
synchronization (GDS) enables you to efficiently load, cleanse, harmonize, and aggregate
data from various internal and external sources. It also provides the data infrastructure
to enable you to distribute that information to the right user, at the right time,
even across corporate boundaries.
Our account manager now will be able to get volume, revenue, and cost of sales information
for his accounts.
3. mySAP CRM: Tactical Planning and Analysis
The next step is to add a planning application on top of SAP BW that links tactical planning
with execution. SAP Advanced Planning and Optimization (SAP APO), mySAP Customer Relationship
Management (mySAP CRM), and others are designed not only to support the specific analytical
capabilities a company will be seeking, but also to function as part of a single architectural
platform that has been systematically designed to connect with the other components of a company's
enterprise management platform, thereby delivering improved TCO (total cost of ownership) value
for the support teams.
Within the trade promotions management milieu, mySAP CRM is the Marketing and Sales solution that enables key figure planning of volume, revenue, and spending, not only along a customer hierarchy but also by several product categories. Moreover, mySAP CRM will automatically convert the planned sales deductions into sales conditions, which are used later in the invoicing process. Such a link is mandatory for being able to compare planned versus actual data on a single promotion level. Our account manager can use this information to evaluate trade promotions and sell them more effectively to the retailers.
4. BW-BPS: Integrated Business Planning and Budgeting
Beside a clear organizational framework along one or several hierarchies, historical data as reference
points in planning are required. Here, the power of BW-BPS (Business Planning and Simulation) comes
into play. BW-BPS allows a company to establish a consistent planning process along hierarchies, using
historical sales and budget data as reference points. The benefit is that trade funds are allocated
top-down in an optimal way to different sales channels and accounts.
Trade promotions planning, for example, must be embedded into an overall sales and budget planning process, as these promotions drive substantial sales volume, and cost as much as 25 percent of the overall sales revenue. BW-BPS ensures that our account manager's plan is in line with the overall company objectives and that trade promotions are an integral part of this plan.
5. Advanced Analytics: Predictive Forecasting
Once the architecture and analytic applications are in place, you can bring to bear the full potential of
this system to not only tell you how successful your existing practices are, but to predict how successful they are likely to be in the future.
For example, understanding in advance when to increase
or decrease investment in a promotion in order to
generate optimal sales volumes — that is
the dream of our account manager. Using the Data
Mining Workbench in SAP BW, our account manager
can find models and statistical methods to calculate
an expected value from historical data.
Most companies want a TPM application platform that presents
an expected volume outcome using historical data from both external and internal sources, as well as sophisticated algorithms that can relate the different data points and draw out the cause and effect that lead to a predictive forecast of consumption or volume.
Armed with these forecasts of volume, spending, and profit, our account manager can create different promotion scenarios with varying tactics, and select the most appropriate promotion to present to his customer.
The Analytic Application Design Process
Analytic applications are the interface that presents overview and summary information to the appropriate business role, be it a CFO, a vice president of marketing, a plant manager, sales representatives, or, in the case of our example, an account manager.
The design of analytic applications should
be simple — less is more! The application
must present the user with the key metrics
of his or her area of responsibility
to understand whether and where to take action.
It must highlight areas of concern and opportunity,
as well as indicate when performance is on
track, to enable fast decision making (see Figure
|A Well-Designed Analytic Application Using SAP's Visual Composer Front-End Tool
Good analytic application design should consider the following factors:
The end user — Which users and business roles are going to use the analytic application? What information is most important to those end users? SAP Analytics applications provide preconfigured KPIs and business intelligence content. Our account manager, for example, needs to monitor sales volume and delivery service, control promotional return on investments, and act
on pending financial disputes, and can do so through analytic applications.
Structure — What will the end user look at first? What are the primary pieces of information? What is secondary, perhaps contextual, information? What
interaction will enable the user to improve the "speed to decision"? The answers to these questions allow analytic applications to be built with navigation tailored to specific user role definitions. For example, daily status reports on volume, revenue, and profit get
prominent space and are clearly separated from the results of an in-depth trade promotion analysis in our account manager's analytic application.
Visual design — What is the best way to visually present this business information so that it results in efficient decision making? Would this information be more clearly presented as an interactive chart or a static table? Would the user be better served by receiving an exception alert than by viewing a graph? SAP tools enable personalization to configure analytic applications to match individual preferences of how information is captured or presented.
User interaction design — When ready to make a decision, can the user get to the appropriate application or solution to take action in the most efficient manner? This step deals with navigation tools such as radio buttons, drop-down boxes, or action buttons.
Remember that an effective analytic application is just one tier of a four-layer approach to analytics architecture (see Figure 1), but is all the user will ever see.
Analytics that Work for Your Business
A rock-solid operational IT landscape supporting your daily business processes is key for success. But of even higher importance is understanding how your business operates and identifying the
critical decisions that have to be made, especially the ones related to industry-specific processes unique to your line of business. By following SAP's roadmap for developing a decision support blueprint, your company can more effectively bring the power of operational IT landscapes into play. Once these decision support processes are understood, the information required to conduct the business becomes apparent for inclusion into the platform, thereby connecting all the dots.
For more information about SAP's industry-specific approach to analytics, please
visit www.sap.com/solutions/analytics/index.epx, and for more on SAP for Consumer
Products, visit www.sap.com/industries/consumer/index.epx.
Wolfgang Peter is the Vice President of Strategies and Strategic Business Development IBU of Consumer Products and Life Sciences at SAP. Having been with SAP since 1990, Wolfgang also served as the Vice President of Consumer Industry Solutions within the IBU Consumer Products and Pharmaceuticals. Wolfgang has a degree in Informatics, Management, and Applied Mathematics from the University of Economic Sciences in Berlin.
Dr. Uwe Scheerer is ERP and Analytics Solution Manager for Consumer Products and Life Sciences at SAP. In his more than seven years with SAP, he has been in charge of BI content development for CP manufacturers from the first days of SAP BW, particularly for the integration of syndicated data like ACNielsen. Prior to working with SAP, he held various IT positions in the consumer products and life sciences industries. Uwe received his Ph.D. in Mathematics from the University of Heidelberg.
Adams is the Solution Principal of Consumer
Products Integrated Sales and Marketing
at SAP America, Inc., focused on providing
thought leadership, field enablement,
pipeline/marketing, and sales support
for the Consumer Products industry. In
his more than five years at SAP, Gary
has filled a number of Director and Architect
roles — from supporting
CPG and CRM/Analytics solutions to marketing,
pre-sales, sales, PSO, and development.
Gary brings more than 23 years of CP
Sales and Marketing experience to SAP
after receiving a bachelor's degree in
Business Administration from Grand Valley
State University in Michigan.