From Discounting to Dialogue: Making Value-Based Pricing Work in Complex B2B Sales

That tension captures a central challenge in value-based pricing: sellers talk about value while buyers see a cost line item. Closing that gap requires a different way of understanding, modelling, and communicating value across long, technically complex buying cycles.

The experience shared by Dr. Alexander Neber and Ian Ambler, senior leaders from SLB, at Manufacturing Pricing Excellence 2026 – Power of 50 shows what it takes in practice. 

Clarifying Value in a Long, Multi-Stage Lifecycle

In the energy sector, the asset lifecycle stretches from subsurface modelling and drilling to production and ongoing optimisation. Each stage involves different teams, budgets, and risk profiles. The spend is heavily weighted towards production, but value creation depends on decisions made much earlier.

That makes pricing decisions unusually exposed. A mispriced offer at the modelling or engineering phase can distort margins for years, while buyers struggle to compare offers on anything other than day rates, licences, or headcount.

To address this, the SLB team reframed pricing as part of a value cycle spanning:

• Customer success – defining what success looks like in measurable terms for the operator, not the vendor.
• Engineering and delivery – ensuring the technology and services can credibly deliver those outcomes.
• Pricing – capturing a fair share of that value, aligned with the customer’s perception, not internal cost models.
• Value modelling – pre-building scenarios and business cases before conversations with customers begin.

They started quantifying value at workflow level: who does what, how often, with what efficiency gain, and what that translates to in monetary terms.

Turning a Hard-to-Sell Platform into Business Cases People Can Buy

A revealing test case was the industry’s Open Subsurface Data Universe (OSDU) – a common data platform initially driven by Shell and supported by cloud providers such as AWS, Microsoft and Google. While the standard promised interoperability and easier asset transactions, it was an unfamiliar concept for many operators and a difficult story for account managers to sell.

The early pattern was familiar in many B2B settings: sales teams led with the platform name and technical architecture, struggled to articulate concrete impact, and then resorted to discounting to get deals over the line.

The shift came when the team stopped trying to sell OSDU and instead built a library of workflow-specific business value use cases. For some international operators, this meant mapping and monetising individual projects, ranked by:

• User groups involved (for example, data managers, domain leads, data users).
• Frequency of use in real studies.
• Expected efficiency gains (for example, a 50% time saving in data discovery).
• Associated dollar value per project.

Some projects, like improving data discovery, generated clear and significant business value and were visible to senior stakeholders. Others, like data clean-up, were necessary but low-visibility and low-return from the customer’s perspective.

Two important implications for industrial sellers:

1. Not all use cases are equally valuable in the eyes of the customer. Value-based pricing requires prioritisation and willingness to walk away from technically elegant but commercially weak projects.

1. Starting with a small number of high-certainty, high-visibility use cases helps rebuild trust after long, complex pre-sales efforts. After 18 months of workshops and technical deep dives, the team deliberately proposed projects they knew they could deliver quickly to re-establish credibility.

From Spreadsheets to Interactive Value Conversations

The practical barrier to value-based pricing in many organisations is operational: models live in opaque, fragile spreadsheets that only a handful of experts can use. Asking an account manager to run a customer through value using a 20-tab Excel file is a non-starter.

Initially, SLB faced exactly that situation. The first-generation value calculators were large, manually built models that took weeks to assemble. They worked, but they were too slow and too specialist to scale across a large salesforce.

Two shifts made the approach usable in live sales discussions:

• Adoption of dedicated value-selling tools integrated into internal systems.
• Use of AI to shorten model build time from weeks down to two to four hours for a tailored calculator.

New models are now designed to be used in front of customers, not hidden in the background. Instead of presenting a static business case, sales teams can adjust parameters on the fly and explore what if scenarios together with the customer.

This interactive format has a subtle but powerful effect. Customers are more inclined to challenge assumptions, correct baseline data, and volunteer their own numbers. That improves model accuracy over time and, more importantly, creates ownership.

As one of the leaders noted: “Better to be generally correct than precisely wrong.” The aim is to start a serious discussion about value where the customer feels comfortable saying what seems wrong and then replacing the vendor’s assumption with their own data.

Challenging Internal Assumptions and Defending Higher Prices

Value-based pricing is often presented as an external exercise, but in practice the internal battle is just as difficult. Cost-plus habits, fear of losing deals, and a belief that the product isn’t mature enough can all drag prices down before the customer has even seen the proposal.

Value-based pricing only works if internal stakeholders are prepared to:

• Question long-standing reference prices and discount patterns.
• Accept that different customers may value the same solution very differently.
• Price to the customer’s perceived value, not internal comfort levels.

That requires evidence. Carefully documented workflows, external benchmarks, and a growing library of validated customer cases gave SLB’s pricing team enough credibility to push back when internal instinct said something was too expensive.

Embedding Value Thinking into Sales, Not a Specialist Corner

Perhaps the most difficult part of the shift was organisational, not technical. For the first years, the value-modelling work was treated as a side project, intellectually appreciated but not embedded into the sales motion. 

Over time, three practices helped move value-based pricing from a specialist hobby to an accepted way of working:

1. Selective deployment, not one-size-fits-all

The team focused on accounts with a partnership mindset and where trust levels were high enough to survive a misjudged slide or an imperfect workshop. They accepted that this approach would not suit every buyer or every account manager.

2. Visible commercial wins

They used unsolicited value-based proposals to introduce new solutions to 50 selected clients, quantifying the expected impact per client based on size and operations. The response rate was unusually high: 35 engaged, and 5–6 deals closed faster than the normal sales cycle. Having tangible wins made other account managers more willing to experiment.

3. Continuous education and tooling

What began as scattered conversations has evolved into structured training. Today, the company’s sales academy ensures new account managers are exposed early to value interviewing techniques, customer-centric metrics, and the use of calculators. On the operations side, the same methods are now used internally to justify investments in proposal factories and automation, framing time savings for pre-sales teams as measurable business value.

The process is still ongoing, supported by a new sales leadership willing to revisit systems and incentives. But the direction is set: pricing is no longer just a number attached at the end of a proposal; it is the outcome of a dialogue about measurable outcomes that matter to the customer.

Conclusion

The SLB experience underlines that value-based pricing is a capability built over time.

That capability rests on a few concrete foundations:

• A clear map of workflows, users, and efficiency gains that can be monetised credibly.
• Tools and models that are fast to build, simple to use live with customers, and open to challenge.
• A salesforce trained to ask uncomfortable questions and to listen for what value means in the customer’s own terms.
• Internal pricing and leadership teams willing to abandon legacy price anchors when evidence from the field shows customers are prepared to pay more.

As customer workflows, business models, and pricing structures grow more complex, the temptation will be to fall back on discounting to keep deals moving. The more strategic response is to do the harder work: quantify, test, and debate value in the open with customers and inside your own organisation.

Those who invest in that discipline will not only improve margins; they will change the quality of their customer relationships from arguing about price to collaborating on outcomes.