White Paper Channel Data Management: Enabling Data-Driven Decision Making

WHITE PAPER

Channel Data Management: Enabling Data-Driven
Decision Making

Sponsored by: Zyme Solutions
Gerry Murray
January 2016

IDC OPINION

Manufacturers are increasingly reliant on channel partners to accelerate revenue growth and open
new markets. However, channels are typically underutilized and manufacturers' processes that support
them are poorly managed. This is because many manufacturers lack the channel data needed to
create actionable insights. Leading manufacturers have realized the only way to accurately understand
the channel is through data. Manufacturers are adopting channel data management (CDM) as a
means to transform how they manage key channel business processes. CDM is a set of technology
capabilities and best practices that simplify and standardize the collection of a wide range of channel
data at scale and use it to drive channel performance and optimize channel-related processes.

Traditionally, manufacturers have relied on products with a strong brand value to open markets and
drive the channel business model. They have rolled out programs to engage and incent channel
performance. But it is getting much harder to differentiate based on just products and programs.
Ultimately, the business relationships between partners and manufacturers will determine long-term
channel growth and performance. The nature of those relationships will hinge, in part, on how
effectively manufacturers leverage partner data to drive key internal processes such as:

 Sales execution and coverage models
 Post-sales service
 Incentive and loyalty programs
 Finance, risk, and compliance
 Supply chain, inventory, and distribution
 Channel marketing
Many vendors do some, or even all, of these things very well for some of their partners — usually the top
5–20%. But very few vendors are able to scale best practices across the entire channel population. As a
result, latent revenue and market share are buried in underperforming channels and latent inefficiencies
and costs are buried in suboptimal channel management processes. IDC's Channel Data Management
maturity model provides a road map for companies to develop a mature channel data management
function, which is essential to competing at the scale and speed today's channel requires. A mature CDM
function can dramatically extend the reach and capability of your channel management practices,
enabling you to get the best out of the best partners and leave the rest to your competitors.

January 2016, IDC #US40629815

IN THIS WHITE PAPER

This white paper presents a method for establishing channel data management as a core competency
across all channel-facing departments. It includes a maturity model for driving excellence in strategy,
people, process, technology, and data workstreams. Companies that embrace a new approach to
channel management based on data-driven decision making will develop stronger relationships with
stronger channel partners than their rivals. Companies using this model are gaining channel capacity
in a time of extraordinary transformation.

SITUATION OVERVIEW

Channel partners are vitally important sources of revenue, strategic support, and customer experience.
In spite of the channel's tremendous role in overall business performance, it is often under-resourced
and inadequately managed. This is especially true for companies that established their channels to sell
physical products, whether widgets or boxed software. In these models, channels typically were
considered a mere fulfillment arm. The attitude of many manufacturers was, "We gave you great
products and a strong brand, now go sell stuff." In an era when product release cycles were measured
in years and solutions were relatively simple, that attitude worked pretty well.

Today, the channel is vastly more competitive and complex. Large manufacturers can have channel
populations in the tens or hundreds of thousands, making it difficult to optimize performance for all of
them. Top-tier partners have extraordinary market power, making it extremely important to recruit,
retain, and optimize the best channel partners. New technologies such as mobile, social, Internet of
Things (IoT), 3D printing, and big data are changing customer behavior, blending product categories,
blurring market definitions, and opening up new revenue streams. As a result, partners are under
pressure to master the skills needed to deliver new solutions, market to new customers, and run new
business models. Manufacturers that guide partners through these challenges will gain share, loyalty,
and revenue at the expense of those that do not. But doing so requires manufacturers to master an
increasingly complex world of channel data. Key drivers of complexity in channel data include:

 The number and variety of entities reporting data — distributors, TAPs, alliances, resellers,
VARs, and service providers

 The volume and variety of data types needed — activation, consumption, and opportunities
 The depth of data (e.g., serial number, deal registration, and end-user data)

The magic ingredient is data. Imagine having the financial, operational, and behavioral data on
partners to optimize new product launches, margin splits, inventory turns, coverage models, and
channel programs. Imagine being able to show partners — no matter how new or small or niche their
focus — how other partners like them have achieved high return on investment (ROI) on their business
with you. This is all possible, but it requires a new approach to channel data management, one that
goes beyond ad hoc, fragmented, and periodic reporting to a model where data exchange is
embedded into the relationship and data management is supported by dedicated infrastructure and
best practices. Key questions that we address in this document include:

 How can manufacturers progress through IDC's Channel Data Management maturity model?
 How can manufacturers leverage partner data for competitive advantage?

 How can manufacturers get partners to participate?

 What are the benefits for partners?

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Progressing Through IDC's Channel Data Management Maturity Model

At even the largest, most leading-edge companies, channel data management is in its nascent stages.
Companies typically lack the organizational expertise, process controls, technology infrastructure, and
data management practices necessary to fully leverage channel data throughout the business. As a
result, this leads to poor decision making in areas such as:

 Sales execution: Unable to match MDF to bookings and hard to enforce price and discount
policies and partner reviews based on gut checks

 Post-sales support: Don't know the end customer, unable to upsell, and unable to validate
warranty claims

 Incentives and loyalty: Incorrect partner payments

 Finance: Unable to produce accurate sales forecasts and business plans and slow to
adjudicate partner payment disputes

 Supply chain: Unable to analyze how much product partners have on hand

 Channel marketing: Programs are generic, effectiveness is hard to measure, and ROI is
unknowable

Practitioners we spoke with are aspiring to or are in newly created (two years or less) global CDM roles,
but few of them have the dedicated resources and authority to be truly successful. Leadership and
executive sponsorship are essential but are not enough. The transformation requires an organizational
commitment. People must be assigned to own the processes. Then the processes can be defined,
optimized, and automated. Technology must be brought in to support the new processes and generate
the data necessary to deliver insights into partner performance. Data is the final, but most important
workstream. It will provide the scalability needed to better manage, support, and enable every partner,
not just those that justify dedicated human resource commitments. But the data cannot be effectively
captured and leveraged until significant changes are made in the technology platform, organization, and
processes. Table 1 provides a detailed description of the key stages in this journey.

©2016 IDC #US40629815 3

TABLE 1

IDC's Channel Data Management Maturity Model: Detailed Description by Stage

Stage 1: Stage 2: Stage 3: Stage 4: Stage 5:
Ad Hoc Managed Optimized for Scale
Opportunistic Repeatable

Strategic Start-up Extend Channel Corporate Identify and continuously
vision mode product marketing/ owner to create deliver the most effective
People marketing to management enterprise support to all channels;
Process the channel asserts efficiencies and consume channel data in all
leadership strategic downstream business
Technology alignment process to deliver value
Data
No dedicated Driven by Departmental or Corporate team Global channel data leader
Capability resources product business unit (BU) under sales VP with sponsorship and
groups or regional CDM resources
teams

No clearly Ad hoc data Single Centralized Enterprise/global processes
defined capture and department to channel data for data collection, analysis,
processes limited use consolidate that and use cases with SLAs
cases channel data and departments across functions
expand data- can leverage to
driven use cases drive specific
use cases

Uncertain Existing back- Departmental Channel data Channel data management
what systems end systems systems of record management platform implemented
are being to house dominate (CRM in platform enterprisewide
used to fragmented sales, ERP in implemented in
capture channel data finance) BU
channel data

No one Limited, Emergent Enterprise/master Analytics exposed to partners
knows what poorly standards for channel data to propagate best practices
data is managed channel data management and drive performance at
captured or channel data validation, best practices for scale; data is accurate and
where it is enrichment, and validation, decision grade; connecting it
governance enrichment, and back to master data is
governance important so that it can be
used in all downstream
systems

Opinion- Collect POS Weekly updates Support for Partner data captured via
based and inventory with support for global data automated partner
channel data monthly multiple data collection submission portal with no
decisions in predefined collection formats standard and manual steps; attention to
templates and modes of advanced frequency of data collection
transmission collection and depth of incoming data
methods

Source: IDC, 2015

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In any maturity model, it is important to benchmark yourself against industry norms and best practices.
In CDM, you would benchmark things such as your coverage and latency of tier 1 and tier 2 data, the
kinds of data you collect, the accuracy of the data you collect, the compliance of your partners with the
process, and your ability to leverage the data in downstream processes to drive business value.

Benefits for Manufacturers

Channel Marketing

 Customer segmentation is the capability to classify your prospective and current customers and
create groups of similar customers based on their behavioral and demographic attributes. It is
used to make key business decisions for effective marketing, promotions, and product planning.

 Partner segmentation is the capability to segment partners and assign tiers by sales
performance, order history, or other value measures and to profile partners based on sales
performance. Partner segmentation data can be used to set or revise sales targets, analyze or
define partner engagement models, map coverage to market segmentation, and improve the
ROI for the channel incentive program.

 Campaign management is the capability to design, execute, and manage campaigns to deliver
the right offer via the right channel at the right time and maximize profits. It consumes channel
data to "close the loop" and match sales data to cost data to determine the ROI for the campaign.

Sales Execution

 Deal registration is the capability to identify deal registrations and match them to actual sales
through partner-reported point-of-sale (POS) data. It is used to validate and pay incentives for
the deal registration based on the actual POS-reported sale. It calculates close rate and cycle
time of a deal, the "net, net price," and supports the automated closure of the deal registration
and automated auditing of incentive payments.

 Channel sales performance management is the capability to aggregate channel performance
across a geography, a segment (i.e., retail), and/or globally. It is used to drive sales
performance in the channel by providing granular data on sales and inventory management.

Post-Sales Service

 Installed base via POS is the capability to populate installed base records using clean and
enriched POS data. It can be used to create serial number installed base records from POS
data; match activations, license, and other customer data; track the asset; and identify
additional service to customers.

 End-customer visibility is the capability to collect POS data with end user and serial number
information to identify the end user of the device or asset within the installed base. It is used to
identify the channel "route to customer" to generate leads and target marketing campaigns into
the installed base.

 Warranty and returns management is the capability to validate whether the product sold
follows the terms and conditions of warranty or not (e.g., product manufactured should be sold
only in the United States; if sold outside the United States, warranty is not applicable). If
warranty conditions are fulfilled, so is the ability to derive the validity period of warranty.

 Upsell and re-engagement is the capability to build a detailed profile of the installed base
(e.g., product, device identifiers, service, and warranty expiration dates) to identify sales
opportunities for additional product/services and the route to customer. It can be used for
supporting upsell and cross-sell alerts and the advance notifications of upcoming renewal
expiration dates to reengage with customers and eliminate any lapse in service and/or
unnecessary fees.

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 Incentive and loyalty is the capability to pay partner incentives from POS data or inventory
data submitted by the partner without the administrative burden of a claiming process. It is
used to accelerate partner payments and reduce the cost of partner incentive programs. It
supports the ship and debit process, special pricing, net-net valuations, and other incentive
plans based off of sales and inventory data.

Finance, Risk, and Compliance

 Revenue recognition is the ability to use the sell-out POS data and to reconcile sell-in/sell-out
data in order to accurately recognize revenue from channel sales net of all MDF and channel
incentives spend. It is used by finance to recognize the financial statement revenue or internal
business unit revenue.

 Financial planning is the capability to monitor financial planning and budgeting items from POS
and inventory data reported by channel partners. It is used to extend the financial planning to
include channel sales and incentives to better predict the financial performance of the enterprise.

 Channel audit is the ability to aggregate sales by partner, inventory, and risk alerts in a
package that can be provided to internal or external auditors to complete channel compliance
audits in an effective and efficient manner. It is used to focus audits on high-risk partners and
high-risk transactions and to reduce the time to audit these partners and/or transactions.

Supply Chain

 SISO inventory reconciliation is the capability to analyze reported sell-through information
with inventory data to enhance profitability. It is used to detect variances within defined
tolerance limits for validation that the channel partner sales and inventory data are in sync
with. It supports the identification of grey market activities and high-risk partners as well as
improves overall data quality.

 Demand forecasting is the capability to consume granular POS data to quantify future demand
at a very granular level. It is used to align inventory balances with predicting future quantities
demanded by sold-to customer or end customer. Accurate forecasting will reduce inventory
balances, reduce stock-outs, and identify excess inventory for supply chain actions.

 Inventory tracking is the capability to analyze the current inventory level with recent sales
history to determine the number of days of inventory (inventory aging) at the current sales
level. It is used to identify excess inventory, reduce inventory aging, and avoid inventory write-
offs. For retail channel partners, store-level POS and inventory data should provide channel
visibility to the larger retail chains.

 Stock-out avoidance is the capability to minimize the occurrences of stock-outs at the point of
sale by understanding product availability within the channel to identify locations with low
volumes earlier. It can be used to increase revenue by providing stock at locations where sales
would otherwise be lost and reduce the logistics costs associated with accelerated shipments.

 Sell-in/sell-through analysis is the capability to link the sell-in and sell-through POS data to
provide channel visibility from sell-in to end-customer sale or activation. It is used to drive
visibility to channel inventory and overall channel sales.

 POS returns and optimization is the capability to evaluate the rate of product returns to
manufacturer, identify specific high-rate partners, and understand the reasons for the return. It
can be used to reduce the associated costs of returns via early detection of potential product
issues and abnormal partner return rates.

 Logistics and inventory optimization is the capability that provides the POS and inventory data
to supply chain modeling to reduce the overall number of inventory moves to achieve the
optimal cost of logistics and inventory.

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Getting Partners to Participate

Large distributors and partners are likely prepared to deliver a well-defined set of sales and marketing
data. Smaller partners with limited resources, however, will need a tangible and immediate benefit and
a very low overhead process to participate fully and consistently. The general rule for channel data
should be that everything that goes out to partners should be designed to bring data back. The four
broad categories of ways in which manufacturers can capture partner data are:

 Contractual obligation. Data should be part of the partner contract. This approach is usually
already in place with the largest partners and distributors. Contractual reporting should cover
all the data attributes required by the manufacturer such as point of sale, inventory, part/serial
numbers, customer identity, and MDF spend. Key to effective data provisioning by partners is
the accuracy, completeness, and timeliness of the data. The best practice in this regard is for
weekly updates. Performance against these requirements should also be factored into how the
partner receives rewards or penalties relating to incentives, certifications, go-to-market funds,
and so forth.

 Operationalized data capture. One of the most difficult types of partner data to capture is
marketing and sales activities. To facilitate this, companies should redesign the partner portal
as a SaaS platform that provides a wide range of functionality. The ideal platform will
consolidate all of the interactions with partners by offering personalized access to content and
transactional systems, as well as the ability to execute customer interactions such as
marketing campaigns. By virtue of this consolidation, it captures an increasingly large portion
of partner activities and provides a continuous flow of valuable data to inform channel
marketing and management.

 Partner scorecards. Many companies use partner scorecards, but they are typically designed
around lagging indicators that are based on incomplete, outdated, and inaccurate data. A
CDM process will enable much richer and more useful scorecards to be developed. A critical
component of the partner score must be related to the data provisioning process itself.
Partners should be scored on the accuracy, completeness, and timeliness of the data, which
can be linked to a number of valuable perks: MDF allocation, prompt payout processing, and
access to greater data services.

 Data as a service. A more advanced method is to externalize the database of partner
performance data and make it available to partners in a way that captures even more data
from more partners. By offering access to the data to partners, manufacturers can deliver
specific insights to them on how they can better run their businesses. Partners can query the
database for detailed benchmarks on the financial, operational, and behavioral characteristics
of very similar peer groups. Of course, the level of detail they get in return depends on the
level of detail they provide. As a result, the database is in a virtuous cycle of enrichment. They
should be able to get insight into a wide variety of strategic and tactical questions such as:

 How many people do I need in marketing, sales, technical, and support roles?

 What level of skills and training should people have?

 What marketing activities are most effective?

 What sales methodologies and plays are most effective and at what stage?

 What manufacturer resources and networks should staff be utilizing most frequently?

©2016 IDC #US40629815 7

OPPORTUNITIES

Benefits for Channel Partners

While the benefits to internal departments that interact with channel partners are significant, the real
payoff for channel data management is in driving the partner performance curve. By gathering more
detailed data on a broader range of partners, manufacturers can get more revenue from their existing
partner base. The key is for manufacturers to leverage their unique position at the center of the partner
universe. No other company, including your distributors and partners, can possibly have the same
level of insight into how different types of partners perform and why. Armed with that data,
manufacturers can start to identify who the highest-performing partners are and the best practices for
partners like them. These insights can be used to show underperforming partners, specifically how
they can boost their ROI on their relationship with the manufacturer — how should they invest the next
dollar in the relationship: Marketing campaigns? Sales training? Technical certifications? Hiring staff?
Recommendations can apply to every role in the partner organization and might include any or all of
the following:

 Marketing: Improving competencies, longer-term campaign planning, and new accounts or
buyer types; leveraging social and mobile channels; and understanding buyer's journey,
product mix, pricing, marketing technology or services, customer data management practices,
and so forth

 Sales: Updated or more pervasive sales training, new sales plays, and improved qualification
milestones

 Technical sales: Advanced certifications and more pervasive technical training

 Support: Upsell skills

 Executive management: Balancing staff resources

This highly personalized guidance can bring underperforming partners closer to their high-performing
peers. It can be a source of tremendous value and promote loyalty that product and programs alone
cannot. Key benefits for partners include:

 Improved cash flow and product availability

 Proactive help to reduce inventory levels

 Benchmarking performance against peers

 Data-driven account reviews

 More effective collaboration to grow business

Of course all this data sharing must be conducted within a good channel conflict structure so that
partners are not helping their direct competitors. But the experience of one partner in one region can
be highly beneficial for partners in other regions with similar business and market profiles. The ability
to propagate best practices with data enables manufacturers to optimize channel recruitment.

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FUTURE OUTLOOK

Companies must adopt a new data-driven model for channel engagement:

 Enterprise/global leadership role and team
 CDM platform for data collection, aggregation, analysis, and management
 CDM governance to maintain completeness, accuracy, and timeliness of channel data
 Data-driven channel management processes and investment models across functions
 Virtuous cycle of information exchange with channel partners

Leading companies are starting to appoint global heads of channel data management, assess the
(topically sorry) state of their partner databases and data management practices, and deploy solutions
to provide a channel data management platform. These companies are exerting organizational,
process, and technological influence across a wide range of departmental areas — product marketing,
corporate and field marketing, sales, sales operations, and regional channel management. They are
aggressively pursuing the vision of stage 5 maturity (refer back to Table 1). In large organizations,
progress will be measured in years, giving first movers significant market advantage. IDC recommends
that to compete, companies must take the following actions (at a minimum) over the next few years:

 Now
 Establish a channel data management organization.
 Decide where the channel data management leadership should be positioned — in sales or
under the CEO.
 Assess channel strategy and objectives against the current channel data management
organization and processes.
 Develop urgency and a new story line to move company culture to a channel data
management mentality.
 Assess the current state of your partner portal technology and the governance structure
for capturing and managing partner data.
 Expand partner advisory boards to include representatives from all segments of the
partner community.

 Next budget cycle
 Develop a plan to consolidate the organization's channel data management infrastructure.
 Establish key organizational interlocks between all partner-facing departments with
associated service-level agreements (SLAs), where appropriate.
 Develop standard taxonomy and governance models for partner data, and roll out globally
across systems.
 Plan to establish an analytics function (staff, tools, and governance) to support internal
and external analytics requirements.

 Over the next one to two years
 Adopt a data-driven approach to everything related to channel management, marketing,
and enablement.
 Reveal insights that both reinforce and challenge current thinking on what drives channel
revenue.
 Encourage partners to use your data to help them better run their businesses.
 Promote your ability to provide business insights as a key differentiator, and socialize success.

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CHALLENGES

Companies are not able to perform mission-critical business operations because of lack of channel
visibility. For example, they are not able to:

 Accurately detect and prevent overpayment of incentives/discounts
 Understand drivers of supply and demand across the globe, within specific regions or

countries, branch locations, or end-customer demographics
 Pinpoint the amount of inventory in the distribution system
 Get timely, detailed insight to identify and propagate best practices needed to drive partner

performance
 Perform partner profiling and segmentation and measure partner satisfaction
 Make confident, data-driven decisions on revenue recognition and reserves

CDM can be a large undertaking for companies that have neglected their channel management
processes over the years. A culture of ad hoc decision making can be hard to change. But technology
is one of the most effective catalysts for change. New systems demand new thinking about how work
routines, holistic processes, and business outcomes can be forged into a core competency. New CDM
solutions such as those from Zyme that provide scalable channel data management capabilities can
be rallying points for channel-facing functions to come together.

Another key challenge is getting partner participation. The CDM program needs to be supported with
marketing and training for distributors, VARs, resellers, and integrators. Every new partner should get
a standard training package explaining the data requirements and usage policies. Every partner
account manager (PAM) or equivalent should also receive training and support resources to help them
assist partners in achieving the highest data provisioning scores they can.

CONCLUSION

By using CDM solutions such as Zyme's, companies can get unprecedented insight into large-scale
channel populations and leverage their position at the center of their channel universe. In addition to its
CDM platform, Zyme provides a global channel directory of over a million partners, support for a wide
range of partner data formats, and a methodology for ensuring partner reporting compliance. With a
deeper understanding of customers, manufacturers can improve regional sales performance and
product planning. Finance and IT benefit from more efficient data collection and financial reporting
enabled by CDM. Other key benefits include:

 Drive channel revenue
 Lower inventory costs
 Market more effectively
 Rationalize partner investment
 Increase compliance

Technology is only one piece of the project, but it is the organizing principle around which change
happens in the organization, the processes, and the data related to channel partners.

©2016 IDC #US40629815 10

About IDC

International Data Corporation (IDC) is the premier global provider of market intelligence, advisory
services, and events for the information technology, telecommunications and consumer technology
markets. IDC helps IT professionals, business executives, and the investment community make fact-
based decisions on technology purchases and business strategy. More than 1,100 IDC analysts
provide global, regional, and local expertise on technology and industry opportunities and trends in
over 110 countries worldwide. For 50 years, IDC has provided strategic insights to help our clients
achieve their key business objectives. IDC is a subsidiary of IDG, the world's leading technology
media, research, and events company.

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