Selling

Could a New Channel Model Lead to Sales Amplification?

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Over the years, I have helped successful companies and start-ups improve and strengthen their Channel and Strategic Alliances programs. Those companies do a great job closing deals but usually have concerns about not generating or receiving enough new business leads. Or, they develop strong relationships with one or two vendors, only to find later that a key vendor has been sending deals to a competitor.

Word cloud for strategic thinking.

Most traditional channel models support Distributors, Resellers, OEMs, and ISVs. The business mainly flows upwards to the main vendor. If that vendor has popular and widely used products, then business can be good because of sufficient demand. But when that is not the case, your sales pipeline usually suffers.

Doing something the same way as everyone else may not be a bad approach when there is enough business for everyone, and your growth goals and aspirations are aligned with your competition.

Sales Channel business is usually not the main source of revenue for most companies, but it does have the potential to become the largest and most scalable revenue source for nearly any business. Just think about the money left on the table by not adopting a growth mindset and executing a new and better strategy.

In the summer of 2016, I attended the “Sage Summit” in Chicago. It was impressive to see the Sage Group’s efforts to build, strengthen, and protect their Customers and Channel Partners community. They tried to foster higher levels of collaboration between the various types of partners – implementation services, consulting, staff augmentation services, complementary product vendors, etc. They had created their own highly successful Business Ecosystem, which is an excellent proof point.

When designing a channel partner program, my focus has always been on finding the balance between promoting and protecting the partners’ business and helping ensure that the end customers have the best experience possible (and have some recourse when things do not work out as expected). There are a variety of methods I have used to accomplish those goals, but the missing component has always been the inclusion of a systematic approach to seed relationships between those partners and facilitate an even greater volume of business activity.

Nearly a year ago, I began working with a management consultancy run by Robert Kim Wilson, which has a business vision based on his book, “They Will Be Giants.” I will provide links for this book and other relevant resources at the bottom of the post. Kim asserts that Entrepreneurs with a Purpose-Driven Business Ecosystem (PDBE) are more successful than those without one, providing examples to prove his point. Having experienced Kim’s PDBE, I see how purpose fosters trust and collaboration.

As I did more research, I found that, especially over the past two years, a lot of focus has been placed on Business Ecosystems and Business Ecosystem Organizers (such as Sage in the earlier example). Those findings reinforced the PDBE approach, and external validation is always good.

It is just as important from my perspective that this concept applies to businesses of any size, and it is especially helpful to small to midsize businesses. The fun part for me is exploring a specific business, analyzing what they do today, and quantifying the benefits of adopting this new strategy.

So, how does this new type of Business Ecosystem work?

  • The Business Ecosystem Organizer expands the overall network, vets new “Business Ecopartners,” and provides a framework or infrastructure for the various Business Ecopartners to get to know one another, exchange ideas, and discuss opportunities.
    • This can become an incredibly sustainable revenue source for companies willing to invest in the necessary components to grow and support their Business Ecosystem.
  • Business Ecopartners will have access to trusted resources to augment existing business and take on new, bigger projects by leveraging the available expertise.
    • Suppose that you have products or services that work with commercial CRM (Customer Relationship Management), ERP (Enterprise Resource Planning), or SCM (Supply Chain Management).
    • You have seen a growing demand for functionality that relies on highly specialized technologies like:
      • Cryptocurrency support.
      • Blockchain for financial transactions and things like traceability in your supply chain or IoT data.
      • AI (artificial intelligence) and ML (machine learning) to detect patterns and anomalies – such as fraud detection, Deep Learning/Neural Networks for image recognition or other complex pattern recognition.
      • Graph databases to better understand a business and infer new ways to improve it.
      • Knowledge Graph/Semantic databases to assist with Transfer Learning and deeper understanding.
    • Building these practices in-house would not be practical or cost-effective for most businesses, so partnering becomes very attractive to your company.
      • This type of business can also be very attractive to a Business Ecopartner because someone else handles sales, billings, account management, etc.
  • Other Business Ecopartners could leverage your products or services for their projects and engagements, thus becoming another source of revenue.
  • By leveraging this network, your business can compete on imagination and innovation – which could become a huge source of differentiation from your competition.

Value realized from this New Business Ecosystem model:

  1. These new sources of business and talent can become a real competitive advantage for your business.
  2. This becomes the source for Sales Amplification because your business is, directly and indirectly, expanding its reach and growth potential.
  3. The weighted (based on capabilities, capacity, responsiveness, and Ecopartner feedback) Business Ecopartner network model could lead to exponential business growth – a winning strategy for any business.

References:

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What are you Really Selling? (hint – solutions)

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It is interesting to see Sales and Marketing people still focusing on features, performance, cost, and even value without creating a linkage to what that means to a company from a business perspective. Once you understand what your prospect is buying and why they need it, you can connect with them meaningfully to increase your win rate.

Pot of Gold

A sales adage from the 1940s (source) asserts, “No one wants a drill. What they want is the hole.” Today, that basic understanding of why people and companies buy is often lost in sales and marketing messages. Sales success is all about solving problems and satisfying needs.

Several years ago, my team and I were selling a new Analytics Database that was genuinely different. Still, our message was identical to every other database vendor – “70% – 100% faster than every other product.” It is nearly impossible to differentiate your product using a non-differentiated message. Don’t treat your product or service as a commodity if it is not one.

I flipped the messaging to focus on business needs. We created a weekly webinar focused on Why Fast Matters. Query response time is important, but responsiveness to customer needs and requests is essential. What if they did not need to wait a week or two to have new indexes created or a month to have a Star Schema updated? They could just run queries as-is, maybe wait a minute instead of a second or two, and have what they need then and there. That message resonated; we sold the first 50% of that product globally. When the Australian team began using our messaging, their sales also increased. Funny how that works.

Effectiveness is all about results and intended outcomes. Efficiency is about achieving those results with the least time and effort invested. It doesn’t mean that we are looking for a lazy approach to find a win. Instead, it is about identifying repeatable patterns that circumvent unnecessary activities, accelerate the sales cycle, and minimize related costs. 

The way to help yourself understand what you are selling is to view things from your prospect’s perspective. What struggles are they likely facing? Where are the greatest opportunities to help their type of business? Are you analyzing data to attempt to assess their unmet needs? Your insight can become a huge differentiator, especially if you can teach them different and better ways to do something (ala the Challenger Sales Model).

What is the difference between your prospect company and its main competition? This analysis requires a general understanding of the problem space and a more specific understanding of the prospect company, its history, and 2-3 main competitors. It also requires an honest account of how your company and products compare to the competition so that you can play up your strengths and limit your investment in areas where the fit is not as good.

The next item to focus on is messaging. Below are a few examples from my career –

  1. Analytics & Big Data – The focus here is often on data volume, the currency of the data, speed of queries, cost, maintenance, and downtime. Those things become essential later in the sales discussion, but initially, companies want to know what problems their product or solution will solve.
    • Some of my fastest deals sold because I demonstrated ways to make better decisions faster and/or identify minor problems before they had the chance to become major problems. Avoiding problems and unplanned outages were critical elements of the messaging.
    • In one case, I closed a significant deal in less than three months by focusing on how a company could provide customers with five years of transactional data. Those customers could use the data to make better purchasing decisions in less time than it took the current system to analyze six months of data. Their sales increased after implementing this modernized system. Helping their customers make better buying decisions faster was the winning message.
  2. Embedded Products – While many companies focus on APIs, features, or cost per unit, I would focus on how the product I was selling made things better and easier to manage for improved Customer Support and Customer Satisfaction.
    • I closed a $1.1 million deal in less than two months to a medical device company by focusing on the life cycle of those devices (often 10-15 years) and how their customers needed consistency from machine to machine. Consistency over time was the winning message here.
    • After being approached by a Defense Contractor for a relational database product for a new Flight Simulator system, I changed the discussion to the complexity of flight control systems, the need to correlate 30+ operational systems in real-time, and the importance of taking a verbal command and translating it to specific commands for each related system. That led to selling a NoSQL product ideally suited for this complex environment. Letting our software handle the highly complex workload helped us win this deal.
  3. Consulting Services – These were not contracting or body shop services (commodities) but actual Business and Technical Consulting services with high visibility and impact. In these cases, expertise, experience, and having a track record of success in different but demanding scenarios provided confidence. These were often multi-phase engagements to prove our value before making a significant commitment.
    • In a bid against two well-established competitors, we won a deal with a large Petroleum company worth nearly $500K. The proposal included information we uncovered about the system and use case and later verified with the prospect, a section on our people and past projects, and a high-level project plan with firm-fixed pricing. We won the bid, and I later discovered that our cost was $50K higher than the largest competitor and $100K more than the other competitor. The customer told me, “Your proposal demonstrated the understanding of who we are and what we need, and that confidence provided the justification to select your company and pay a premium to have the job done right the first time.”
    • My first million-dollar deal was with a company where we demonstrated our ability to solve problems. They knew they needed assistance but were not exactly sure where. I created a “Pool of Days” concept that provided flexibility in the work performed (task, deliverables, and scheduling) but had minimum monthly burn rates and an expiration date to protect my company. The winning messaging this time was that flexibility and the ability to accommodate changing needs without introducing significant risk or additional cost were better ways to buy consulting services. This approach led to many other deals of a similar nature with other companies.

The common theme is helping companies solve their specific business problems from these examples. Even when technology was central to the message, focusing on better outcomes for that prospect and their customers was essential. Value matters, but positive results and better outcomes matter even more for purchasing decisions.

Nobody wants to be responsible for taking a chance on a new vendor and be responsible for a high-profile failure. Helping instill confidence early on makes a huge difference, and following through to successful implementation results in happy customers who become loyal customers who provide references and referrals.

Success starts with selling what you can do from a business perspective for your Prospects. You are solving their problems with solutions they need and avoid getting lost in the noise of the unfocused messaging from most of your competition.

Good Selling!

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Shouldn’t Sales Forecasting be Easy? What about Accuracy?

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I’m sure that everyone has read articles that state some “facts” for managing your “sales pipeline” or “sales funnel.” Things like needing 10x-30x of your goal at the start of the process, down to needing 2x-3x coverage at the start of a quarter to help increase your odds of achieving your goal. Now, if it was only that easy…

First, what are you measuring? The answer to this question is something that anyone with a sales quota should be able to succinctly answer. For example, are you measuring?

  • Bookings – Finalized Sales Orders
    • What happens when Sales Operations, Finance, or Legal push back on a deal? You have a PO, but has the deal really been closed?
  • Billings – Invoicing Completed
    • This includes dependencies that have the potential to introduce delays that may be unexpected and/or outside of your control.
  • Revenue – An in-depth understanding of Revenue Recognition rules is key.
    • How much revenue is recognized and when it is recognized varies based on a variety of factors, such as:
      • Is revenue Accrued or Deferred? This is especially key for multi-year prepaid deals.
      • Is revenue recognized all at once – such as for the sale of Perpetual Software Licenses? (even this is not always black and white)
      • Is revenue recognized over time – such as with annual subscriptions that are ratable on a monthly basis?
      • Is revenue based on work completed / percentage of completion? This is more common with Services and Construction. Combining contracts, such as selling custom consulting services with a new product license, can complicate this.
      • Are there clauses in a non-standard agreement that will negatively affect revenue recognition? This is where your Legal team becomes an invaluable contributor to your success.
    • Cash Flow – Is this really Sales forecasting?
      • The answer is ‘no’ in terms of Accounting rules and guidance.
      • But, if you have a start-up or small business, this can be key to “keeping the lights on,” in which case the types of deals and their structure will be biased towards cash flow enhancement and/or goals.

My advice is to work closely with your CFO, Finance Team, Sales Operations Team, and Legal team to understand the goals and guidelines and then take that one step further to create policies that are approved by those stakeholders and are then shared with the Sales team to avoid any ambiguity around process and expectations.

So, now the hard part is over, right?

Diagram showing upward trend over the word Sales.It could be that easy if you only have one well-established product, a stable install base, and no real competitive threats, where the rate of growth or decline is on a steady and predictable path and where pricing and average deal sizes are consistent. I have not seen a business like that yet, but I would have to believe that at least a few exist.

Next, what are you building into your model to maximize accuracy? Every product or service offered may be driven by independent factors, so a flat model that evenly distributes sales over time (monthly or quarterly) is just begging to be inaccurate. For example:

  • One product line that sells perpetual licenses may depend on release cycles every 18-36 months.
  • A second product line may be driven mainly by renewals and expansion on fairly stable timelines and billings.
  • A third product line may be new with no track record and in a competitive space – meaning that even the best projections will be speculative.
  • Finally, services could be associated with each product line and driven by more dependent and independent factors (new implementations, upgrades, implementing new features, platform changes and modernization, routine engagements, training, etc.)

Historical trends are one important factor to consider, especially because they tend to be the things you have the greatest control over. This starts with high-level sales conversion rates and goes down to average sales cycle, seasonal trends, organic growth rates, churn rates, and more. Having accurate data over time that can be accurately correlated is extremely helpful. But factors such as Product SKU changes, licensing model changes, new product bundles, etc., increase the complexity of that effort and potentially decrease the accuracy of your results.

Correlating those trends to external factors, such as overall growth of the market, relative growth of competitors, economic indicators, corporate indicators (profits, earns per share, distributions, various ratios, ratings, etc.), commodity and futures prices (especially if you install base tends to skew towards something like the Petroleum Industry), specific events, and so forth can be a great sanity check.

The best case is that those correlations increase your forecasting accuracy for the entire year. In all likelihood, they provide valuable inputs that allow you to dynamically adjust sales plans as needed to ensure overall success. But, making those changes should not be done in a vacuum, and communicating the potential need for changes like that should be done at the earliest point where you have a fair degree of confidence that change is needed.

There will always be unexpected events that negatively impact your plans. Changes to staffing or the competitive landscape, reputational changes, economic changes, etc., can all occur quickly and with “little notice.” That is especially true if you are not actively looking for those subtle indicators (leading and trailing) and nuances that place a spotlight on potential problems and give you time to do as much as possible to proactively address them. Be prepared and have a contingency plan!

Forecasting accuracy drives confidence, which leads to the ability to do things like getting funding for new campaigns or initiatives. Surprises, even positive ones, are generally disliked simply because the results are different than the expectations, which begins to fuel other doubts and concerns.

Confidence comes from understanding, good planning, helping everyone with a quota, and the teams supporting them to do what is needed when it is needed to optimize the process and then to have an effective approach to determine whether deals really are on track or not so that you can provide guidance and assistance before it is too late.

It may not be easy, but it is the thing that helps drive companies to the next level on a sustainable growth trajectory. In the end, that matters the most to the stakeholders of any business.

As an aside, myriad rules, regulations, and guidance statements are provided by various sources that apply to each business scenario. I am neither an Accountant nor an Attorney, so consult with the appropriate people within your organization or industry as part of your routine due diligence.

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Good Article on Why AI Projects Fail

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high angle photo of robot
Photo by Alex Knight on Pexels.com

Today I ran across this very good article as it focused on lessons learned, which potentially helps everyone interested in these topics. It contained a good mix of problems at a non-technical level.

Below is the link to the article and commentary on the Top 3 items listed from my perspective.

https://www.cio.com/article/3429177/6-reasons-why-ai-projects-fail.html

Item #1: 

The article discusses how the “problem” being evaluated was misstated using technical terms. At least some of these efforts are conducted “in a vacuum.” Given the cost and strategic importance of getting these early-adopter AI projects right, that was a surprise.

In Sales and Marketing, you start the question, “What problem are we trying to solve?” and evolve that to, “How would customers or prospects describe this problem in their own words?” Without that understanding, you can neither initially vet the solution nor quickly qualify the need for your solution when speaking with those customers or prospects. That leaves room for error when transitioning from strategy to execution.

Increased collaboration with Business would likely have helped. This was touched on at the end of the article under “Cultural challenges,” but the importance seemed to be downplayed. Lessons learned are valuable – especially when you are able to learn from the mistakes of others. This should have been called out early as a major lesson learned.

Item #2: 

This second area had to do with the perspective of the data, whether that was the angle of the subject in photographs (overhead from a drone vs horizontal from the shoreline) or the type of customer data evaluated (such as from a single source) used to train the ML algorithm.

That was interesting because assumptions may have played a part in overlooking other aspects of the problem, or the teams may have been overly confident about obtaining the correct results using the data available. In the examples cited, those teams figured out those problems and took corrective action. A follow-up article describing the process used to determine the root cause in each case would be very interesting.

As an aside, from my perspective, this is why Explainable AI is so important. Sometimes, you just don’t know what you don’t know (the unknown unknowns). Understanding why and on what the AI is basing its decisions should help with providing better quality curated data up-front, as well as identifying potential drifts in the wrong direction while it is still early enough to make corrections without impacting deadlines or deliverables.

Item #3: 

This didn’t surprise me but should be a cause for concern as advances are made at faster rates, and potentially less validation is made as organizations race to be first to market with some AI-based competitive advantage. The last paragraph under ‘Training data bias’ stated that based on a PWC survey, “only 25 percent of respondents said they would prioritize the ethical implications of an AI solution before implementing it.”

Bonus Item:

The discussion about the value of unstructured data was very interesting, especially when you consider:

  1. The potential for NLU (natural language understanding) products in conjunction with ML and AI.
  2. The importance of semantic data analysis relative to any ML effort.
  3. The incredible value that products like MarkLogic’s database or Franz’s AllegroGraph provide over standard Analytics Database products.
    • I personally believe that the biggest exception to this assertion will be from GPU databases (like OmniSci) that easily handle streaming data, can accomplish extreme computational feats well beyond those of traditional CPU-based products, and have geospatial capabilities that provide an additional dimension of insight to the problem being solved.

Update: This is a link to a related article that discusses trends in areas of implementation, important considerations, and the potential ROI of AI projects: https://www.fastcompany.com/90387050/reduce-the-hype-and-find-a-plan-how-to-adopt-an-ai-strategy

This is definitely an exciting space that will experience significant growth over the next 3-5 years. The more information, experiences, and lessons learned are shared, the better it will be for everyone.

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