1. Making Data Meaningful
FIVE CORE COMPETENCIES OF ENHANCED DATA ANALYTICS FOR
CHANNEL MANAGEMENT
Whitepaper | November 2015
®
2. Similarly, Gartner has also identified a similar trend. In a
recent survey analysis conducted on customers rating their
advanced analytics platforms, 53% of respondents view
advanced analytics as critical to their organizations’ success,
with the majority of the remaining respondents realizing value
and ROI from advanced analytics (Figure 2).2
These reports
illustrate the trend of enhanced analytics across all functions
and operations of IT investments in organizations. This also
pertains to the channel.
Although the use of business intelligence (BI) and investment
in related solutions within organizations isn’t at all new, there is
an urgent shift toward the democratization of information and
in changing the method in which BI is accessed, controlled,
and distributed throughout the organization.
The rise of “big data” brings organizations closer to deeper
levels and wider breadths of customer and market information
that they did not have readily accessible in the past. The
Internet of Things (IoT), consumerization of IT, and cloud
business models are changing the ways in which information
is collected, shared, and used and demand a faster reaction
time for organizations to adapt to keep pace with changes
in the market. Limiting access to the wealth of information at
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Business Intelligence for the Business User
The utilization of data and business intelligence throughout the enterprise continues to grow in importance. In fact, according to a
recent report from leading industry analyst Forrester, most companies recognize the importance of data and analytics, ranking the
‘increase of our use of business intelligence, big data, analytics, and decision-support tools and services’ as their top “critical priority”
for the next 12 months (Figure 1).1
Figure 1: Forrester Research, Inc.: Companies Recognize the Importance of Data and Analytics
1 Forrester Research, Inc.: “Maximize Your Chances of Business Intelligence Success in a Customer-Centric World”, The Business
Intelligence Playbook for 2015, September 24, 2015.
2 Gartner: Survey Analysis: Customers Rate Their Advanced Analytics Platforms, September 22, 2015.
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hand lends itself to a “you don’t know what you don’t know”
risky obliviousness at the business user level, which can
lead to missed opportunities, slow and reactive – vs. pro-
active – decision-making to customer and market needs,
and an antiquated approach that hinders productivity and
a companies’ ability to differentiate to customers. This
tends to occur when information isn’t readily available to the
appropriate business users throughout the organization in a
real-time, user-friendly, actionable fashion. Rather than relying
solely on a traditional and centralized approach of confining
and protecting data access only to C-level information
technology executives, companies are realizing the benefits
of taking a more decentralized approach and are making
investments towards putting the intelligence into the hands of
the business leaders.
This decentralized approach enables controlled access to
defined information sets that matter to the different business
users across the organization. It allows executives and
channel chiefs responsible for sales, marketing, finance,
and legal operations, as well line of business (LOB) decision
makers, to make informed decisions about channel programs,
partners, and product sales with insights that are data driven.
According to Gartner, the BI and analytics market will grow
to $20 billion by 2019, and BI solutions are undergoing their
biggest transformation, as new spending is controlled by
business users wanting more agility and flexibility to analyze
and visualize data.3
Business users are demanding and
gaining control within organizations to have access to data
in order to improve their ability to impact performance in
achieving organizational goals and objectives.
This white paper explores the importance of enhanced
analytics with regards to impacting channel management
strategies, activities, operations, and performance. Data
is meaningless unless it serves purposeful functions in
daily business life such as solving business problems,
understanding business performance, ability to take action
with informed decisions, and assisting in designing future
business plans to ensure revenue acceleration, improved
engagement with partners, and cost control. This paper
introduces five core competencies of enhanced analytics,
discussing specific use cases of how business users can
utilize data daily to enhance their ability to improve channel
management activity and performance across the enterprise.
Channel Complexity Impairs Clarity of
Business Performance
Channel management encompasses multiple processes and
stakeholders throughout an organization that also extends out
to the partner ecosystem. As illustrated in Figure 3, Revitas
Enterprise-Class Channel Management Components and
Workflow4
, such activity contains workflows that integrate with
many of the core operating systems that organizations have in
place today, including CRM and ERP systems.
Information is flowing to and from trading partners for
program definition, partner eligibility, and incentive program
development activity. Once activated, programs then need
to be monitored for performance, validated, and calculated
for processing of payments. Accuracy in calculations for
payments on programs, as well as performing forecasts and
accruals on program performance and activity, occur only
Figure 2: Gartner Survey Analysis: Advanced Analytics Platforms
3 Gartner: Market Trends: Technology Shifts Mean More Venture Capital Investments for Business Intelligence and Analytics Startups,
September 18, 2015.
4 Revitas, Inc. Enterprise Class Channel Management Components and Workflow Diagram, January 2015.
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when such transactional linkages of channel management
activities to both front-end CRM and back-end ERP financial
systems are in place.
With most organizations managing upwards of hundreds
to thousands, to tens of thousands of partners, products,
and programs, the volumes and complexities of transaction
activity and accuracy of the validation processing activity with
back-end financial operations is immense. The clarity in which
business leaders have into the performance of the channel is
often murky or lacking entirely due to such complexities, and
due to use of manual methods for managing channel activity
and operations. The need for access to meaningful data
for analysis and performance measurement within channel
partner and program activity is critical to any organization
deriving revenue from channel partners. There is also a risk in
maintaining compliance without a system in place to maintain
an audit trail and history of data and reporting information
within the channel and with partners.
The costs to organizations lacking clarity into the performance
of their channel operations due to such complexity are quite
high. Recent research from Accenture indicates that most
technology and manufacturing companies generating annual
revenues of $1B or more are deriving up to 80% of revenues
from channel partners.5
With such a large amount of revenue
being derived from the channel, siloed information availability
or high-level data points from product sales or revenues alone
will not be sufficient to enable informed business planning
and decision making. Additionally, findings indicate that most
organizations do not have a full grasp or understanding of the
hidden costs of channel sales. According to Accenture, 3-5%
of revenues are spent on incentive programs, but 10% of such
investments into channel activity are not yielding the expected
return on investment.6
Although the percentages seem
small, the dollars on the table are quite high. If we consider
theoretically a company earning $10B in revenues who is
deriving 80% of revenues through the channel, this equates to
$8B expected earnings through the channel. If 3-5% is spent
on channel programs that equates to roughly $340M, and
10% of an insufficient return on investment results in roughly
$32M on overspend annually – a significant number.
An actual proof point from a Revitas customer that eliminated
such cost, and is achieving actual savings and revenue
generation of up to $100M annually was recently cited in a
report from IDC.7
Enhanced analytics was one of the primary
purchase decision drivers, and resulted in Improved P&L
performance by providing greater visibility into product line
profitability. Intelligence and insight to programs being
rolled out to the channel, and analysis of performance are
imperative business priorities. The ability to understand
Figure 3: Revitas Enterprise-Class Channel Management Components and Workflow
5 Accenture, “Improving the ROI of Channel Incentives”, 2014.
6 Ibid.
7 IDC Health Insights: “Business Strategy: There’s a Hole in My (Revenue) Bucket! Revenue Leakage in Life Sciences — Who’s Plugging the
Holes, and How Can They Help?”, September 2015.
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performance occurring in the channel empowers executives
and business users to uncover the answers to key business
questions based on activity and take appropriate action. With
access to enhanced analytics, they can deliver insight at the
point of impact and make informed decisions around actual
business activity and ensure continuous improvement based
on metrics.
Challenges for Effective Data Analytics
In many cases, organizations find that they have data, but it
is residing in disparate systems and serving linearly focused
business objectives. Data is typically being called upon for
quarterly reports to executive management in a predictable,
canned fashion or is being called upon for reactive analysis
and served up in ad-hoc spreadsheets. Although these
approaches and standard reports are viable for certain
business-as usual-needs, how sustainable are they in today’s
rapidly changing environment? And how meaningful is that
data if it cannot be analyzed in such a manner that a business
user can take action and make informed decisions? Is the
data accurate and based on current business results? Can it
be used to model multi-dimensional measurement projections
based on both real-time and historical activity? Is the data
targeted? Can users perform business discovery analysis
and visualize data from a dashboard view and control panel
at their fingertips in a way that is more meaningful for them?
Can it be combined with other data sources easily to apply
projection models? What if business users were empowered
with self-service access to such meaningful data from their
channel activity? It is clearly evident that these questions are
top of mind to most businesses today, and that companies are
making concerted cross-functional efforts and investments
in solutions that will grant them the ability to maximize their
potential with meaningful analytics. A summary of key
challenges and hurdles many organizations are facing today
with regards to limitations with enhanced analytics include:
• Data may be housed somewhere and available, but it is
unclear where and in what format
• Compliance is at risk without an integrated system
to manage reporting or maintain an audit trail of
transactional data and activity
• It is time consuming and difficult to access data due to
internal gatekeepers and processes
• Data is not presented in a way that is meaningful to
business needs and therefore in-actionable
• Data lives in different systems, across departments,
and in spreadsheets and is often not consumable in
order to make an impact
• Reports are requested ad-hoc or received with
rigid parameters and real-time access to data is not
available
• Data resides in endless columns and rows and it is
difficult to visualize
• Data is linear in scope, and limited in ability to compare
multi-dimensionally, such as across business units,
products, partners, and timeframes
Five Core Competencies of Enhanced
Data Analytics for Channel Management
Data means different things to different people across the
functions pertaining to channel management. The following
Five Core Competencies of Enhanced Data Analytics for
Channel Management introduce methods of how business
leaders and users can utilize information on a daily basis to
perform their business needs:
1. Data Analysis for Trends Identification
2. Data Modeling for Financial Forecasting and Accruals
3. Data Exploration for Business Discovery
4. Data Visualization for Controls and Dashboards
5. Data Reporting for Format and Consistency
Information becomes more valuable when it is in the hands of
the right people, at the right time, and for the needed purpose
to deliver results for enhanced performance management
through better decision making. Let’s explore each core
competency with regards to the business intelligence and
performance management attributes through identification
of business value factors, use cases, data elements and
dimensions, as well as some illustrative representations of
analytics capabilities .
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Business Value:
• Enable business users to perform deeper and wider analysis on critical business information
• Slice and dice information to investigate for multi-dimensional analysis and data insights from different perspectives
• Drill down from summary levels to transactional level details
• Build charts and graphs for visual analysis
Data Elements and Dimensions:
• Analyze and measure business performance by program, partner, and product
• Identify and replicate top performing programs; modify or eliminate programs that do not yield sufficient returns
• Identify and direct resources to top performing partners; help underperformers strengthen results
• Measure product profitability more accurately and determine strategies for improvement
Core Competency #1: Data Analysis for Trends Identification
Almost every business user would benefit with access to business intelligence for trends analysis. Trends can be provided by external
sources, such as industry analysts, for agnostic monitoring of overall market and competitor activity, however trends analysis on
activities internal to your organization with regards to performance are of equal and even greater value. Providing business users with
access to real-time targeted data tailored to their business function allows them to understand what is working and what isn’t working
on a deep and wide scale within a particular business context.
Use Case
A business analyst on the channel marketing team would like to have access to data so that
he can prepare weekly trend reports for senior management delivering more insights into
channel performance. Channel teams are typically developing incentive programs based on
blind performance in the channel, and often without having the ability to know if a particular
incentive program investment or partner is yielding the expected sales results at the product
level. Questions at hand may include: What business impact is pricing having on a specific
chargeback? How is one program performance ranking among other programs? How does
one partner rank among all other partners based on total volume over the past 6 months? The
business analyst would like the ability to aggregate, filter, and pivot the data to uncover trends
on a daily basis, and also have the ability to drill down into details easily and quickly.
Programs Trend Analysis: Quickly and easily monitor
performance of Incentive programs tracking spend
quarterly, annually, daily. Quickly identify anomalies in
spend over time so that corrective action can be taken
immediately preventing loss of revenue.
Product Details Example: Drill down into details of
all products within a particular program to easily find
causes of trends. Identify if there is greater spend on a
particular product and investigate the reasons.
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Business Value:
• Replace manual spreadsheets with automated consolidation, collection, calculation, approval, and workflow processes
• Apply complex and sophisticated models to large data sets to perform real-time impact analysis
• Enable organizations to respond faster to changing market conditions through creation of multiple evaluation and forecasting
scenarios
• Provide positive proof of compliance with audit trails and revision history
• Improve accuracy of budgeting and accruals
Data Elements and Dimensions:
• Analyze historical incentive transactions to calculate accruals for chargeback liabilities
• Monitor incentive accruals status and checkpoints
• Evaluate chargeback units, actuals, averages, rates, and percentages for accurate incentive forecasting
Core Competency #2: Data Modeling for Financial Forecasting and Accruals
Financial data modeling is a cardinal business practice and imperative for informed decision making and performance management.
Modeling enables business users to understand what actions should be taken based on a trend or a particular business performance
issue, concern, or objective. Financial data modelling is complex, and is typically performed by a financial or business analyst who
brings expertise in mathematics and accounting.
The utilization of spreadsheets is popular and accustomed in most organizations due to the user-friendly interface and programming
tools. However, spreadsheets are susceptible to errors and it is difficult to detect when errors occur. Spreadsheets are also often
utilized cross-departmentally, living on individual desktops or importing data feeds from back-end financial systems. Data remains
stagnant and is not connected to real time feeds. This introduces compliance risk due to the lack of audit capability – knowing how we
arrived at a value of accrued dollars and why and by whom changes were made. Financial data modeling for channel management
activities are closely inter-related with activities at the CFO levels due to budgeting purposes, but are often times “best guestimates”
of actual channel business activity. Inaccurate processes and systems for data modeling activities present significant risks to
compliance and successful business planning.
Incentive Forecasting: Combine read-only data with
new data you may want to input. Apply forecasting
rate to calculate out future incentive spend for each
program or trading partner.
Blueprint Scenario Modeling: Reference
implementations to create blueprint scenarios of
consolidated incentive models for customers.
Use Case
A financial analyst is interested in understanding the costs related to investments made in
incentives and accuracy of payment validations to partners. He also needs a close estimate
for forecasting accrual funds for chargeback liabilities based on historical transactions. He
often requests data pulls from back-end ERP systems and manually building data models with
additional data inputs from sales and marketing and other ops systems. He needs to marry
historical data with real time performance metrics and apply complex models to multiple data
sets in order to perform analysis activities, which is typically a lengthy and multi-step process
involving multiple business units Blueprinting potential projection models and scenarios and
conducting discussions on pre- and post- deal analysis with business leaders and clients are
essential for ensuring long-term business planning alignment.
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Business Value:
• Create custom reports to better address the individual concerns of the business users
• Access operational reporting views with each product and solution
• Remove the complexity of the underlying transactional data schemas and table joint logic
• Enable business user with the ability to determine what is important to them within their custom reports
Data Elements and Dimensions:
• Any data point should be accessible to business users, and derived from historical systems, data marts, and transactional systems
• Operational meta-data layers based on specific business contexts
• Join enterprise data with local data assets
• Comparisons against multiple data dimensions for exploration and analysis
Core Competency #3: Data Exploration for Business Discovery
Business discovery and data exploration capabilities are at the heart of enabling intelligence for the business user to enhance
performance while engaging in daily activities. A business user wants to see all the data that is available to them and have the
capability to filter down into various data dimensions to access information that is relevant for today - such as current pricing of
eligible products on a contract. Ease-of-use and fast assembly of targeted, relevant information allows business users to easily find
what they are looking for. Exploration, visibility, and transparency across multiple data dimensions existing in master data marts assists
business leaders in creating custom reports and in gaining data insights that they may have missed or didn’t realize existed.
Business Intelligence Explorer: Intuitive, easy to use,
drag-and-drop table builder for data discovery activity.
Drill down into transactional data quickly and easily
to find pricing, discount, product ID, status, eligibility,
and more.
Business Intelligence Analyzer: Know what’s working
and what isn’t working to make informed decisions,
with bimodal enhanced data exploration and analysis
integration capability. Quickly identify how a program
ranks among all other contracts based on total volume
over the past 6 months, for example.
Use Case
A marketing director oversees product marketing teams to develop pricing and go-to market
business models for numerous products and services. In addition to working closely with
financial teams for sales and market forecasts, she wants to be able to investigate quickly and
easily into targeted parameters of activity. She needs to have a steady pulse on all products
sales and market performance for high level monitoring, but also so that she can take quick
action to make adjustments to pricing or to an incentive program if needed. She requires
access to a variety of data sets for collaboration with other team leaders on business activity
and must be readily able to understand any performance factors happening in the market on a
daily basis. She must have flexibility in her ability to create customized reports for presenting to
project teams, partners, and end customers.
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Business Value:
• Create dashboards tailored to business users across the organization
• Visually interact with data and key performance metrics
• Modify or change analysis and metrics on the fly Review information remotely with mobile capabilities
Data Elements and Dimensions:
• Dashboard data elements can be custom created to meet the needs of the business user
• Channel management performance dashboards display summaries of performance and trends by program, partner, and
products with drill-down capabilities into details
• Develop dashboards to visualize channel activity by channel partner type such as wholesaler or distributor or to show
corporate-wide performance
Core Competency #4: Data Visualization for Controls and Dashboards
Information that is displayed in a structured and visually appealing manner and that contains the relevant data elements tailored to
the specific business user in an easy-to-understand dashboard is a crowning jewel for enhanced analytics. We mentioned earlier in
this paper that one of the primary driving forces of the increasing trend in enhanced analytics and their transformation is that business
users want more agility to analyze and visualize data. Dashboards empower all business users with multi-touch and multi-dimensional
Key Performance Indicator (KPI) metrics in a visually responsive form so that it is easy to grasp and use in decision-making. Today’s
agile workforce expects information to be presented in a crisp, modern, graphically-rich, and meaningful manner on any device.
Dashboards are also considered to be modular control panels, with functionality that promotes intuitive interaction with data, so that
changes can be made easily to the metrics on the fly.
Channel Performance Dashboard:
Visualize performance across entire
channel activities with customized
dashboards.
Corporate-Wide Performance Overview
Dashboard: Ability to review overall
company margins and evaluate what
types of incentives are being leveraged.
Mobile Analytics: Access business
intelligence quickly, easily and in an agile
fashion to maintain pulse on performance
activity. Grant flexibility in presenting
information to constituents.
Use Case
A sales operations director doesn’t have time to sift through columns and rows of numbers
in spreadsheets to create customized reports. Most of his time is spent in front of existing
customers and channel partners to analyze and evaluate overall business performance and
conduct strategic planning. With his sales operations dashboard readily available on his
mobile device, he can easily present the KPIs and performance metrics with partners during a
value assessment meeting with current, relevant data at his fingertips. Equipped with a visually
appealing Pricing Waterfall, he is able to easily identify to a top performing partner the reasons
for margin erosion and successfully negotiate new contract and pricing terms.
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Business Value:
• Reports can be standardized or custom developed and tailored to the business needs
• Ensure consistency and proof of validation for transactions processing and compliance reporting
• Reports are embedded into each application and pre-configured, and can also be embedded into visualization dashboards or
contract templates
• Reports provide secure and swift access to information to answer questions such as, “How many? Who? How often? Where?
What?” in a reliable format
Data Elements and Dimensions:
• Reports can contain any data elements pertaining to the application and needs of business user
• Reports can be tailored and developed from role-based data elements and metrics per business user
• A centralized report library enables access to reports across application modules in a secure manner
Core Competency #5: Data Reporting for Format and Consistency
Standard reporting continues to be a mandatory and relevant staple for all day to day business activity. Standard reporting ensures
consistency and commonality in metrics within specific applications. Reports are securely and seamlessly executed by role-based
business users from report libraries based on single-sign on authentication. Reports can be both printed or delivered automatically
via email sent to all parties who require the information. Reports answer the expected daily business questions for operations and
should be formatted appropriately and reside within the application so details are easily retrievable.
Standard Product Contracts Report: Review a standard
product contracts report to easily look up information to
perform a business task. For example, to easily find the
rebate price and tier to determine and accurately calculate a
final payment amount on a rebate claim.
Embedded Dashboard Reports: Reports can be embedded
within dashboard visualizations as well as applications for
quick and actionable access to information.
Use Case
A partner is submitting a claim for payment. The contract administrator would like to
confirm the price and tier to determine the final payout. Instead of contacting two individual
departments to obtain a product pricing report and partner program tier report separately,
the contract administrator accesses the reports directly within the application associated for
processing the payment. She autonomously performs her task of to accurately confirm and
calculate the final payment for the incentive.
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Conclusion
Enhanced analytics is becoming more and more critical to
sustaining an organization’s success. Ensuring information
is actionable and accessible at the business user level
is becoming the norm because it empowers the entire
organization to truly understand business performance.
More importantly, business users across the organization
will know how to make a greater impact on improving overall
performance. Application of the five core competencies of
enhanced analytics into daily business activity makes data
more meaningful for your organization and for your users
and makes data available for a variety of uses and purposes.
Organizations more easily improve channel operations, and
enhance partner effectiveness and engagement through
utilization of meaningful data, and actionable intelligence.
About the Author
Revitas is the leading provider of enterprise-class solutions
for channel and contract management, on premise and in the
cloud. Revitas solutions enable organizations to accelerate
revenue through diverse, multi-level sales channels and attain
maximum value from contracts. For over 25 years, Revitas
has empowered companies in channel-intensive industries
to achieve best-in-class performance and sustainable
competitive advantage.
