This new 3 part blog series considers the unique challenges of procuring logistics services. They discuss how new tools can dramatically upgrade logistics procurement processes to deliver extraordinary visibility into supplier costs and performance, and drive significant savings in your supply chain.
When it comes to logistics, the standard approach to procurement has severe limitations. Logistics isn’t a commodity, and the methods that work for commodity procurement don’t begin to get a grip on it.
Consider what an ideal logistics procurement effort could look like:
DISCOVERING entirely new savings and service optimisations by using x-ray analysis of big data sets from the entire industry
PERSUADING colleagues and decision makers in supply-chain management and finance with convincing data and simulations
IMPLEMENTING new procurement arrangements painlessly and efficiently, eliminating leakage losses
VERIFYING ongoing gains and benefits to supply chain and finance teams
How many of those objectives are achievable in a standard approach? If you’ve been involved in logistics procurement it’s likely that you will have experienced something more like this:
DATA FOG: Limited access to data, hands tied in negotiation
RESISTANCE to change from internal teams or individuals; conflict between cost reduction and service levels
LEAKAGE: losses from procurement changes that aren’t implemented well
CREDIBILITY GAP because any gains are difficult to verify to internal teams
What’s more, research shows that logistics procurement is widely viewed as a purely tactical matter – as a matter of doing the same as before but slightly more effectively or economically. But if there’s been one big lesson for business since the beginning of 2020, it’s that fundamental strategic changes are often vital to survival in a pandemic-stricken world, and logistics procurement has a big role to play in making those changes.
So how can a logistics procurement process that has until now been constrained by limited data, unambitious tactical objectives and organisational pushback be transformed into something of much greater value to a business?
It starts with data transparency. Without a complete grasp of all the data, it’s impossible to make the best choices in any kind of procurement exercise. But even though there’s a lot more critical data to assess in a logistics proposal than in a standard commodity contract, logistics procurement professionals are forced to operate in a data-starved environment.
Obtaining comprehensive and accurate data from an organisation’s (often outdated) ERPs can be enough of a problem, but in addition the lack of transparency into supplier data on pricing, services and compliance means any negotiation is asymmetrical – the supplier always knows more than the procurement team. And because the response to each RFP contains thousands of data points, and each proposal is expressed in a non-standard way, the procurement team doesn’t have enough time or resources to fully compare a range of suppliers and make a complete and thorough evaluation of the available options.
Most procurement professionals see these limitations as ‘just the way it is’, and resign themselves to doing the best they can under such unfavourable conditions. After all, the process they follow works well enough for their procurement work in other fields.
"Data fog is a major cause of the modest ambitions ‘baked in’ to most traditional logistics procurement processes."
But now imagine, as a McKinsey procurement paper expressed it, ‘a procurement team so deeply connected to every tier of its supply base that it has access to all relevant data on cost structures, supply availability, lead times, financial and operational risks, and service and quality metrics. This procurement team would be well-positioned to negotiate the “right” prices, instantaneously adapt its own planning, or switch to alternative suppliers in the event of supply shortages.’
Who wouldn’t – the authors ask – be excited to have a ‘supplier x-ray’ like that?
Indeed. But anyone experienced in logistics procurement might be forgiven for thinking that no such thing exists. In the real world, it’s hard enough to sift through the information in a single supplier proposal and evaluate its potential impact on an organisation's complex logistics operations. It’s harder still to request repeated adjustments to the proposal, and re-evaluate over multiple iterations to find the best combinations of value and service. And if a procurement team wants to consider several other possible suppliers as part of the same exercise, the amount of work expands exponentially – not least because of the extreme difficulty of making like-for-like comparisons between non-standardised proposals.
So ‘data fog’ is a major cause of the modest ambitions ‘baked in’ to most traditional logistics procurement processes.
To move beyond these limitations, procurement professionals would require complete visibility into logistics performance and cost data, not just of currently contracted suppliers, but of a gamut of viable alternative suppliers.
They’d also need:
To some, that might seem like a tall order. But this is 2021: the ‘real world’ has changed… and all of this is now readily achievable.
The Procure module of the 7bridges platform uses AI, machine learning and big data analysis to propel logistics procurement onto a new plane of value and effectiveness. With the unprecedented insights and data-driven decision support that this tool provides, logistics procurement professionals can deliver enormous gains, demonstrate value to colleagues, and even make the procurement process an important part of an organisation’s strategic planning capability.
In the second part of our discussion of Logistics Procurement, we survey the pitfalls to be avoided in RFP generation, and the gains offered by working with multiple providers.