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Will digital transformation be the catalyst for adoption of new outcome-based pricing models?

Every day I find myself reading about the developments happening in business-to-consumer (B2C) pricing.

Here’s a sample of those that jumped out recently:

These developments highlight the growing momentum behind providing dynamic, value-based and outcome-based pricing models, a movement being driven by companies’ desires to provide personalized customer experiences at scale.

While this push has been most publicized and noteworthy in the B2C world, driven by the likes of Uber, Netflix and MoviePass, it also consistently permeates the complex business-to-business (B2B) IT products and services world that we focus on. “How do we shift from a cost-plus to value-based pricing model? Are companies really doing outcome-based pricing? Who is doing it well, and for what types of customers? How?” These are common questions vendors are trying to sort through as they change their businesses.

Often, we’ve heard that IT vendors are serious about making outcome-based pricing models work, but the customers are putting the brakes on these types of arrangements. Customers will ultimately balk at the variability and risk of an outcome-based arrangement at some stage of a deal negotiation and push vendors to offer predictable fixed-price engagements. Customers like the idea of not paying when an outcome is not achieved more than sharing the benefit of an outcome that is met, and somewhere in that trade-off the fallback becomes a traditional contractual arrangement.

What’s interesting is that based on recent research, this customer hesitance seems to be abating. In our 2H17 Digital Transformation Customer Research, we asked 165 global enterprises that are undertaking digital transformation initiatives to identify the pricing structures they’ve experienced, and outcome-based pricing emerged as the most common model globally.

As my colleague Jen Hamel points out in the report, “This indicates vendors have become more flexible and creative with pricing to convince clients to take the DT [digital transformation] leap but may see delayed ROI from DT skill investments as revenue depends on project success.”

As digital transformation continues to take root, the question of how vendors can shift to outcome-based pricing will only be asked more frequently, particularly as changes in the timing of revenue recognition from engagements impact vendors’ flexibility around resource investments. We are eager to watch (and to report) as best practices develop and new models emerge and would love to hear about what others think on this topic.

Drop a comment here or email me at [email protected].

 

Pricing research is not always about price

I recently read an article summarizing an onstage interview with Amazon CEO Jeff Bezos at the George Bush President Center. During the interview, Bezos described Amazon’s data mindset:

“We have tons of metrics. When you are shipping billions of packages a year, you need good data and metrics: Are you delivering on time? Delivering on time to every city? To apartment complexes? … [Data around] whether the packages have too much air in them, wasteful packaging … The thing I have noticed is when the anecdotes and the data disagree, the anecdotes are usually right. There’s something wrong with the way you are measuring it.”

This is critical insight for market research practitioners, including those (like myself) focused on pricing. As analysts, we tend to deep dive on the facts and seek hard evidence. We rely on the data to tell the story and articulate the outcomes. Bezos isn’t saying that we should totally discount data. What he’s saying is that data has value when contextualized and re-examined in the context of the actual customer experience.

Pricing is an inherently data-driven exercise. IT and telecom vendors lean on transactional systems, price lists, research firm pricing databases, and other data-centric tools to make pricing decisions and determine appropriate price thresholds. Most of the pricing projects that we do on behalf of our clients start with the question, “Are we competitively priced versus our peers?” That is usually the most basic component of the results that we deliver.

What we’ve found over the years doing this work is that pricing in the ICT space is often more art than science, and that customer anecdotes about pricing are often as valuable and instructive to pricing strategy as the market pricing datasets produced. Our approach to pricing research is rooted in interviews with representatives of the vendor and enterprise customer communities. Often in conducting these interviews, we’ll uncover that the root issues with pricing, which were thought to be associated with the price itself, are often broader issues — something related to value articulation, market segmentation, packaging or delivery efficiency. These aspects influence the customer experience, create pain points, and ultimately dictate willingness to pay and value capture.

When we deliver these results to our pricing research clients, the outcomes are often not only a list or street pricing change, but rather, a rethinking of a broader pricing, go-to-market or customer engagement strategy. Clients will utilize customer anecdotes to rethink how they message a product in their marketing campaigns and content, devise a new approach to customer segmentation, or take a hard look at the delivery cost structure and resource pyramid levels that are driving their price position. In designing pricing research initiatives, we encourage our clients to think more broadly about pricing and incorporate multiple organizational stakeholders into the process, as this can uncover true unforeseen drivers of price position.

How does this compare to your organization’s approach to pricing? How important are customer anecdotes to your pricing processes? Drop a comment here or email me at [email protected].

 

Is the IT hardware market ready for Hardware as a Service?

Hardware as a Service — or maybe you call it PCaaS, DaaS or XaaS — is basically referring to bundling some type of hardware (e.g., phones, PCs, servers) with life cycle services and charging a recurring fee over a multiyear contract. The customer never really owns the hardware, and the vendor takes it back at the end of the agreement.

Sure, it’s not a new concept. But the solution hasn’t exactly taken off like a rocket ship, either. So, is it going to? Maybe. Its initial speed may be more like a Vespa than a SpaceX Falcon, but there are a few things working in its favor.

Why do buyers want it?

  • Retiring hardware is a huge pain. I have talked to IT leaders who have literally acquired warehouse space solely to store old hardware they have no idea what to do with.
  • Making it easier to stay up to date with tech. Management can no longer deny the negative impact on morale brought by an unattractive, slow and/or unreliable device.
  • Automation & Internet of Things (IoT) usher in new capabilities. Who doesn’t want to make managing hardware easier? Hardware as a Service is basically IoT for your IT department. Device management features like tracking device location and health are key functions of many IoT deployments and is a core selling point of Hardware as a Service offerings.

Why do vendors want to sell it?

  • Business models are changing. That darn cloud computing had to come along and change expense models, not to mention make it easier to switch between vendors. From Spotify and Netflix to Amazon Web Services and Salesforce, “as a Service” is second nature to IT buyers in both their personal and professional lives.
  • Creating stickiness. Hardware is more often perceived as “dumb” with the software providing the real value. If you’re a hardware maker (or a VAR), you need to make the buyer see your relationship as one that’s valuable and service-oriented versus transactional.
  • Vendors desire simplicity. Most vendors will tell you they have been building similar enterprise service agreements on a one-off basis for years. These new programs will hopefully create swim lanes to make it faster and easier for partners to build solutions.

Buyers are used to monthly SaaS pricing models, but that’s not really what creates the main appeal for Hardware as a Service. Buyers really want the value-added services and fewer managerial headaches.

So, how’s it going?

As someone who manages several research streams, I get to peek at results from a lot of different studies. Here are a few snippets of things I’ve heard and seen in the last month or so.

  • Personal devices: It certainly seems like there’s the most buzz around PCs, with Dell, HP Inc. and Lenovo all promoting DaaS offerings. I have also heard from enterprises doing initial DaaS pilots with as many as 5,000 PCs, but we seem to still be in very early stages of adoption. Both PC vendors and their channel partners are beginning to report “legit” pipeline opportunities tied to DaaS.
  • Servers: Either outright purchasing or leasing servers is still the overwhelming choice of purchase method for about 90% of IT buyers recently surveyed by TBR. Perceptions that an “as a Service” model will be more expensive in the long run is the main customer concern to date that vendors will need to address via emphasizing the value-added life cycle services.
  • Hyperconverged infrastructure (HCI): A bundle of hardware and a services bundle? This is the bundle of bundles! Not too many HCI vendors are openly promoting an “as a Service” pricing model at this point, but 80% of current HCI buyers in TBR’s most recent Hyperconverged Platforms Customer Research indicated they are interested in a consumption-based purchasing model, particularly to enhance their scalability. About 84% of those surveyed are using HCI for a private or hybrid cloud buildout, so maybe a more cloud-like pricing model make sense. Make no mistake, interest is not synonymous with intent, but it’s safe to say these buyers are at least paying attention to their purchasing options.

My general verdict is that things are still moving at Vespa speed. PCs have a head start over data center hardware based on the concerted go-to-market efforts of the big three OEMs and a consumption model that more closely aligns with the consumer services we’re used to. The second half of this year will be an interesting proving ground to see if the reported pipeline growth is converted to actual customers. Depending on how that goes, maybe we’ll see the data center guys making more serious moves in this space.

What do you think? Add a comment or drop me an email at [email protected].

 

Critical success factors for successful pricing research

In my day-to-day life at TBR, I regularly interact with clients seeking to undertake pricing research. Their needs are varied. Some want to understand pricing for a new product or service or sustain their competitive position for an existing offering, while others seek to design an overarching commercial strategy or to increase the effectiveness of their sales teams by arming them with tactical data and insights — and nearly all are focused on influencing revenue and margin.

Capturing pricing data that can be utilized defensibly for decision making is challenging. All pricing is situational and can be influenced by any number of factors. Pricing decisions influence, and are influenced by, nearly all organizational departments, from sales and finance to product management and business strategy, and thus are often highly politicized within ICT enterprises.

Based on our regular experience in serving the pricing research and consulting needs of our client base across ICT industry segments, we have identified five critical success factors that can help clients navigate these challenges:

  • Start with outcomes: We often find that our customers come to us with a research concept in mind, but not a defined goal or set of operational plans for how the research will be deployed in their organization. Sometimes the request is: “We need to know what vendors like us are charging.” But the real goal of the team may be to answer the question: How can we be more efficient in resourcing deals? By starting with the end goal and use case in mind, we find that we often explore areas adjacent to pricing, and that insights on those topics, in concert with pricing data, unlock business value for our client base.
  • Focus on business impact: For all the research we do at TBR, including in pricing, we advise our clients to frame all research needs around the underlying business impact. We design projects, including the questions we propose to cover in primary research and the data that we seek to capture, to ensure that the recommendations we deliver around pricing aim directly at influencing business strategy, revenue and profitability.
  • Focus on context: Our pricing research methodology relies on interviews with vendors and customers. This approach allows us to capture not only pricing data but also contextual data and insights on topics such as discounting, commercial incentives, pricing structures and portfolios. When paired with core quantitative pricing data, these types of interview-driven insights provide predictive value focused on vendor and customer pricing and consumption behavior.
  • Build market constructs: To normalize against deal-specific influencers that can impact a true view of market pricing, we design our research to focus on deal constructs. These constructs are used in all interviews to ensure apples-to-apples comparisons and that we are characterizing a full spectrum of potential price points. Context on topics such as discounting is addressed through qualitative conversations.
  • Consider adjacent markets: Many times, particularly with clients seeking to stand up pricing models and price levels for new offerings, we find that the direct peer landscape may not be the best basis of comparison. By looking at adjacent offerings and considering how similar-yet-adjacent offerings are packaged and delivered, clients are able to gain a broader foothold in their peer landscape in its entirety, and often identify areas to elevate value proposition and raise prices accordingly.

 

The Business of One era requires new business planning and management practices

A new generation of incredibly powerful, flexible and responsive businesses is reshaping markets. Their ability to serve single customers at scale is what TBR terms the “Business of One.” The environmental forces triggering this shift are vast. Information velocity accelerates globally; digital information expands exponentially; competitive advantage windows compress rapidly; task work automates; acute labor shortages persist in new skill work; and new business risks pressure public policy. In the aggregate this confluence of technology-enabled business factors disrupts traditional business, education and public policy best practices. Technology vendor and enterprise business models must evolve, as evidenced by the market capitalizations of relatively new businesses such as Facebook, Amazon, Apple, Netflix and Google (FAANG) while more established firms have languished. In the Business of One era, success will rest upon rapid iterations rather than deliberate cadences, ecosystem participation for assembling complementary assets rather than amassing scale advantage, subscription monetization cycles rather than transactional product sales, and highly automated processes and customer access points rather than labor-intensive task work and repetitive, overlapping paper trails to establish commercial trust.

Blockchain: The virtual trust backbone for digital commerce

Given the past several decades with the internet, cloud computing and ubiquitous access to data, we are getting closer to frictionless flows of communication and commerce — and getting there faster every day that blockchain permeates financial services and supply chains. But as value flows less from bricks and atoms and more from clicks and bits of digital information, our governance policies and record-keeping systems have not kept pace. Quite simply, humans have been slow to adjust to Moore’s Law, but we are nearly well-conditioned enough to operate faster, and blockchain is the treadmill that will whip into shape the human contribution to supply chain verification and management.