Case Study – TOLL
- Largest logistics company in the southern hemisphere with $0.8B in annual revenues for the 3 divisions evaluated by Pricing Insight
- Sell freight services to approx. 13,000+ customers
- Under significant margin pressure – gross margins of 45% and EBIT margin of 3%
- Engaged Pricing Insight to develop a pricing strategy to improve gross margin
- $8.2M in gross margin profit generated in 12 months on addressable project revenues of $800M
- Program of work undertaken was Project Blackbird – an algorithmic price optimisation program that generates risk free incremental gross margin profit
How to generate an extra 1.5% in gross margin profit in less than one year
10-billion-dollar logistics company undervalues itself by $100M in gross margin annually.
Caught under-pricing red handed
Pricing Insight first became aware of TOLL’s pricing issues when we saw firsthand how TOLL had won a freight contract for a large farmed salmon producer.
Their tender had been 15% below the incumbent suppliers pricing.
In an epilogue discussion with the salmon farm owners, it turns out they would have paid TOLL and extra 5-10% more than their current supplier’s contract pricing just to be rid of them as the incumbent supplier had let them down on one too many occasions.
Toll priced this tender on a cost-plus basis not based on value.
The farmed salmon producer just happened to be a Pricing Insight client at the time.
A simple formula with a use by date
Toll has been a very successful logistics company for many years. Growth has come through a steady but focused acquisition program of smaller carriers.
TOLL has been extraordinarily successful using simple pricing techniques such as cost plus for many years. There has been a strong reliance on the sales reps’ judgement and individual prowess to negotiate a good deal.
In recent years, with demand shifts away from mining and the increasing prevalence of procurement led sourcing, TOLL has experienced margin declines that have substantially reduced earnings.
Cost Plus again
The business, whilst having checks and balances in place such as sign off authority matrices, largely relied on individual salespeople to make pricing decisions.
These decisions mostly relied on Cost Plus mark-up pricing strategies. This approach has both overpriced TOLLs services and crucially under-priced their major contracts which are of significant value.
There were a number of clients in the top 100 of each business unit who were under-priced vs. the value they receive from TOLL. This resulted in many millions of dollars of lost gross margin earnings.
How we came to work with TOLL
Brian Krueger, the then CEO came across Pricing Insight’s algorithmic pricing program Project Blackbird and set up a meeting with his executive team to discuss how this program could improve TOLL’s gross margin profit and earnings.
Several meetings were then undertaken to better understand the current business model and commercial challenges faced by the business.
We determined that there were some serious outages in the pricing policies, pricing methods and analytics. Through further detailed analysis, we concluded there was a substantial opportunity to improve pricing operations was available to TOLL. The management became keen to explore how these improvements could be implemented across the business.
Small steps initially
Our initial work with TOLL was to undertake a comprehensive pricing strategy diagnostic. This pricing diagnostic evaluated pricing at TOLL from a number of areas:
- Pricing Strategy – the market position of TOLL, the types of problems it solves and who it serves in the market best
- Pricing Structures – The price architecture, rate card price differentials for various freight types and pricing differential across customers and geographies.
- Pricing Operations – the tactical pricing decisions, pricing methods and analysis of pricing actions.
The results of this action
We determined the following situation was present post the diagnostic.
- No clear set of value drivers by customer/segment documented
- Value analysis not used to inform pricing or negotiation strategy
- Cost Plus / Flat / One dimensional price increases issued to market
- Decentralised and inconsistent pricing
- Sales almost 100% responsible for price setting
- No clear market positioning
- Misalignment within business units and across business units with regard to price setting, negotiation techniques and perceived pricing power
- Experience and knowledge of customers and market varies widely within each Business Unit
- Limited pricing analytics undertaken due to lack of resources & technical skills
- Limited competitor pricing intel captured
- Limited analysis of customer value drivers to inform quotes / demands for price concessions
This list of pricing operations risks required a proactive and structured evaluation across each of the 3 business units Pricing Insight was asked to evaluate.
Pricing Insight also undertook a detailed analysis of TOLL’s pricing structure, revenue and customers.
We determined that many customer pricing arrangements were inconsistent in relation to each other but also inconsistent with a value framework we had developed to identify pricing risks and opportunities at TOLL.
What we did next
A series of pricing strategy workshops was undertaken using the Pricing Insight framework to guide discussions.
These workshops involved the key stakeholders from each of the 3 business units. The key outputs from these workshops were captured in detail and then evaluated by the Pricing Insight team to validate and refine potential solutions.
A detailed set of recommendations was developed for TOLL’s management.
In parallel sequence, Pricing Insight undertook analysis of all of TOLL’s pricing by customer, freight type, geographic region and a range of criteria that was unique to each customer but captured in the sale reporting system. This analysis involved taking over 700MB of data and determining a new approach to price setting.
Pricing Insight were able to develop a series of detailed recommendations for implementation by the TOLL management team with additional assistance from Pricing Insight.
These recommendations included:
- Develop a structured framework for value that can be applied at a segment or customer level.
- Undertake detailed value driver analysis of accounts in each revenue / margin quadrant to identify common value drivers.
- Build out a check list of value drivers-based Customer Value Canvases developed for key accounts
- Train account reps to understand the fundamentals of customer value and how to extract value confessions beyond traditional sales call dynamics and use this knowledge to negotiate more effectively for TOLL
- Need to segment customers according to the Pricing Insight 36-cube segmentation methodology. [Classifying customers by the key fields of: Vendor, Supplier Partner, Large, Mid Small and Current, New, Lost and Never Won segments]
- Training and education of our sales reps on pricing strategy, value propositions and cross selling techniques
- Re-visit the rate bands to ensure we are bringing optimal prices to market
- Review scope creep risks and identify pricing architecture to capture more value and improve gross margin profit outcomes.
Part Two of Pricing Insight’s engagement with TOLL was to develop a unique pricing algorithm to drive gross margin expansion and gross profit improvements across the three business units.
Pricing Insight were able to identify $8.2M of virtual risk-free margin gains for TOLL using a value-based pricing algorithm developed specifically for TOLL by Pricing Insight.
This margin improvement was generated over the course of the next 12 months as old, flat across the board price increases, were replaced by the algorithmic pricing approach.
Whilst the algorithmic formulae may have been complex with extremely complex data modelling to support the required outputs, the process for TOLL was easy and the usual issues associate with price increases were reduced.
The net outcome for TOLL was a project ROI of over 1,000% in the first 12 months of implementation.
Whilst TOLL is effectively a single service offer – freight from point A to Point B, there are enormous variations in freight types and customer profiles which creates a rich and complex landscape of value combinations.
This complexity means that simple cost-plus mark-up price setting and flat price increases twice per year are not optimal ways to maximise prices, gross margins and earnings.
Freight is often an easily commoditised service. Our research into TOLL’s customer base showed that every customer has a unique freight value profile. IT is this insight that is the basis for price optimisation and underpins the ability to generate gross margin profit improvements.
It was at first difficult to identify the elements that make up a customer’s unique set of value drivers, but with some application of the Customer Value Discovery process, it became easy to see the differences between customers in their value profiles.
In addition to gross margin improvement through algorithmic techniques, the discovery of value also enabled the sales team to then negotiate better prices with more confidence resulting in gross margin improvements and earnings growth.