Developing a Data-Driven Channel Data Management (CDM) Program

Manufacturers who sell through distributors, integrators, resellers, and retailers have traditionally leveraged intuitive, sometimes informal sales processes, driven by sales people who earned their stripes on the battlefield of person-to-person relationships. Manufacturers had very little downstream information, and the data they did have was largely historic – which gave them a backwards-looking view that did very little to respond to real-time channel and inventory needs.

Today, a new “smarter channel” is emerging, which relies on cloud-based processes to gather and manage vast amounts of data from which new business insights can be derived. This new business process discipline, known as Channel Data Management (CDM), takes a forward-looking and in-depth view of the channel. Acting as a framework that allows manufacturers to gather sales and inventory data from distributors and dealers, CDM provides detailed and real-time data that can be used to more effectively manage inventory, sales incentives, marketing programs, and supply chain logistics.

By automatically collecting and managing granular data on sales and inventory, CDM liberates business intelligence and transforms business processes. Large manufacturers use multiple channels to deliver their products to end customers, and each channel is optimized to enable the greatest sell-through and profitability.

In the past, best practices in channel management meant hoping distributors and resellers would send in their reports once a month, and then parse them on a spreadsheet – or having channel managers working the phone trying to keep up with the information about orders, sell through, exchanges, and returns.

The demands on IT managers today have changed this picture completely. Not only are they being asked for greater accuracy and greater speed in producing and communicating data about product in the channel, they’re being asked for much greater visibility into the channel.

In addition to basic numbers about which reseller ordered or returned which products –
a difficult task in itself – IT professionals are also being tasked with making possible a far deeper analysis of what is happening in and across the entire sales and distribution channel, whether that channel spans across the country or around the globe.

Data-enabled organizations demand to know more, and need to know it instantaneously. What was sold? What was returned? How does one region compare with another, or with industry averages? How is this new product model performing compared with the previous model? Which resellers are truly devoted to the product line, and which are merely on board to squeeze the most dollars out of the incentive programs?

The value of deeper channel visibility goes well beyond the channel itself. What do the numbers from the first month of sales say about demands on OEMs or for manufacturing capacity? Should inventory be balanced from one region to another, rather than shipped to one and returned from the other? How will trends in the channel impact the need for operating capital?

Until recently, none of this data was easily available, but was buried in spreadsheets and the hip pockets and intuition of channel managers. In the past few years, CDM has emerged in response to demand from enterprises seeking to understand more about their markets, channel partners, and channel marketing expenditures.

CDM: A Logical Extension to CRM

CDM has a lot in common with Customer Relationship Management (CRM), yet there are distinct differences. CRM is more applicable to direct sales organizations, using technology and processes to improve relationships with current and future customers to increase sales and enhance customer loyalty. CDM, on the other hand, manages relationships not with end customers, but with channel partners. Ultimately, the goal is the same – to optimize sales performance and revenues.

CRM became a valuable tool, by helping organizations gain intelligence and insight into the direct sales channel, and better understand what customers are buying and in what vertical markets. Today, that type of insight is being extended into the indirect channel as well.

CDM helps manufacturers be more effective at managing channel relationships by making sure that partners are nurtured and compensated appropriately, and ensuring that the large amounts of data required to support the manufacturer-channel partner piece of the value chain are accurate. This information – in addition to providing a better foundation for compensation – also provides both the manufacturer and its channel partners with useful marketing data that allows managers to more accurately focus the attention of sales people to territories, opportunities, and individual customers.

Uncovering Hidden Diamonds

As manufacturers expand into new channels, a wealth of point of sale (POS) data accumulates. This channel data potentially includes deep insights and market intelligence into who, what, when, where, how, and why specific products or product lines are being sold – and conversely, where and why certain products are not selling. For too many companies, this rich knowledge slips through the cracks, never gets thoroughly analyzed, and is not leveraged to the fullest extent possible. Ripe opportunities for making better, more informed decisions are lost due to the sheer volume of data, and to their inability to make sense of it.

“Manufacturers are generally trying to accomplish one of two things in the channel,” explained Ted Dimbero, Chief Customer Officer for Zyme Solutions, a developer of cloud-based Channel Data Management (CDM) software. “They’re either striving to drive additional revenue through the channel, or they’re trying to find inefficiencies and reduce the costs of their existing channel programs. Their sales and inventory are one or two steps behind where the real demand exists, and they’re trying to get closer to the edge of the channel and figure out who’s buying their products, why they are buying, and what needs to do be done to move inventory faster.”

Within global distribution channels, a common, significant problem relates to receiving and ingesting data from hundreds or thousands of different resellers and partners, in many different formats, according to Dimbero.

“This often requires looking at millions of end customer and reseller records to figure out where the data came from. Then there’s the ongoing issue of wrong product numbers, descriptions, incorrect part numbers, and on and on. By solving that problem – with a combination of software, algorithms, and specially trained data stewards – a manufacturer can get access to supremely accurate sales and channel data, and that data can be used by IT professionals to fill information gaps for a large number of data consumers across the enterprise. This includes people in finance, compliance and risk management, manufacturing, market planning, service contract renewals, channel sales, incentive program management, and elsewhere.”

Not Every Partner Is Created Equal

Most companies have a selection process for adding new channel partners, and some resellers will always produce better results than others. Manufacturers will design and implement their own channel initiatives, but “customers will ultimately buy from the entity that most directly influences the buyer,” Dimbero observed. “This is often a retailer, reseller, or value-added integrator. Manufacturers need to figure out which partners are most effective, why they are successful, and how they can be incentivized to produce better results.”

Channel incentive programs can consume up to 30 percent of a manufacturer’s revenue, and are often blindly managed without clean, timely channel data to back them up. Market development funds and incentives drive channel sales, but without a deep dive and visibility into channel sales results, it is impossible to understand precisely how effectively the channel is being managed, whether too much is being spent on incentives, and if the funds are being spent in the right way. The new “smart channel” empowered by CDM improves channel visibility with data validation technology that helps to mitigate what can otherwise be an error-prone process.

Top channel performers will organically receive a lot of attention from the sales organization, and may even have dedicated channel managers nurturing them on a daily or weekly basis. How can sales management determine whether too much time is being spent on preaching to the faithful who would out-perform the pack, regardless of how much or how little attention they get?

The concept of focusing a lion’s share of channel resources on a handful of top performers may seem logical to some, but it may also result in wasted resources. Forward-thinking companies should also be growing the long tail of the channel – and that requires deep analysis and dynamically adjusted planning based on accurate, near real-time channel data collection.

Build Your Own, or Leverage a Market Proven CDM Platform?

According to Forrester, of those technology manufacturers that use channel data management software, 80 percent are building their own systems from scratch, compared with 20 percent buying a commercial product. This might work to their detriment, some experts believe.

In larger organizations, home-grown systems may just not be able to keep up. The data collection function might work most of the time, but the data cleansing and data functionality capabilities of proprietary in-house systems are more likely to break down with all of the inevitable data exceptions.

“Anybody who’s tried to cleanse their own channel data has found that this is an IT function fraught with problems before the data gets into the systems, or they have to build a bunch of complicated validation rules,” Dimbero said. “The problem isn’t a ‘set it up and go away’ problem. It’s a constantly messy process, where 10 percent of the partners and up to 20 percent of the SKUs are changing at any time, and it’s a full-time job to keep up with that. This is where even the best IT organizations often fail, if they attempt to do it all themselves.”

Keeping up with a churn of messy data, and the constant flow of new partners and new rules is expensive, and home-grown systems will stop scaling after a while. Many home-grown systems were built to provide an aggregate look at data trends, and they may successfully serve that purpose. But when a company needs to make granular supply chain decisions, it’s necessary to get down to the partner, SKU, and customer levels – including details, such as the city and postal code of each customer. When that form of data is needed, data fidelity becomes more important, and those other systems that were used for aggregate trending become less useful.

A More Effective CDM Strategy

The challenge today for enterprise IT, marketing, and sales executives is to expand the use of data-driven processes within their sales channels to achieve measurable improvements in channel operations. This new data will help refine manufacturing processes, and serve to create vastly improved market intelligence that can be fed into ERP and other planning tools.

In addition, this level of insightful and in-depth real-time data helps manufacturers better understand reseller performance, achieve savings in marketing and compensation incentives, and optimize the channel with better inventory control and product planning. From there, it can be leveraged by senior management to improve overall visibility into channels and markets, driving improved bottom-line results for any company that sells through extended sales channels.

These bottom-line results may include other benefits in addition to revenue growth, such as reduced incentive overpayments, reduction in errors, reduction in time-to-pay partners, and a significant drop in inventory required on hand due to greater channel efficiencies.

“Best-of-breed CDM solutions, built from the ground up for a specific purpose and market-proven by some of the world’s largest manufacturing organizations, are today liberating the valuable intelligence locked in channel data to improve the management of key business processes. In many cases, the financial impact has been significant,” Dimbero added.

Dan Blacharski

Dan Blacharski

Dan Blacharski is an industry observer, writer, and public relations counsel for high-tech firms in the cloud computing space, management consultancies, and outsourcing/managed services providers. He currently lives in South Bend, Ind. with his wife Charoenkwan and their Boston Terrier "Pladook." Contact him at
Dan Blacharski

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One response to “Developing a Data-Driven Channel Data Management (CDM) Program”

  1. Claude Patou

    Hello Dan.
    A bemol. In a car selling business, if CDM don’t include seasons variabilities, a monitored new sell method or management willn’t correctly inform on its performance. All big data CDM has limits if bad parameters.
    Best regards.

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