Buy or build your fuel pricing platform? Part one: build it

Today, fuel retail is a fast-moving, turbulent industry to operate in. So, as a fuel retailer, dynamically managing your pricing can be increasingly complex and time-critical. To keep up with the competition, savvy retailers are turning their attention to data insights, AI, and machine learning to develop and execute more effective pricing strategies and eliminate the guesswork. And if that wasn’t difficult enough, increasing levels of compliance and regulatory requirements elevate the risks of not getting it right.

To arrive at the optimum price and implement quickly, you must consolidate intelligent pricing analytics capabilities with efficient execution in a single platform that works across your entire network of fuel sites. So the real question? Should you build your own pricing system or buy one from a specialist provider?

First, we’ll assess the merits and drawbacks of building your own pricing platform. To read more about buying a platform, check out part two of this blog.

So, if you’re considering building or outsourcing your pricing platform, ask yourself the following:

Do you have in-house talent or a trusted development partner?

The main benefit of building your own platform is that the product is owned entirely by your business, tailored specifically to your needs. But to ensure the end result is fit for purpose, you need high-quality internal talent to specify, build, support and maintain or a software partner you can trust.

Unfortunately, for companies whose core business isn’t technology, software development processes are notorious for being poorly organized, resulting in under-specification, rework and other time-consuming activities.

If you’re outsourcing, consider if your chosen partner has sufficient fuel retail industry knowledge or not; are they a specialist or a generalist? If you haven’t worked with them before, fully outline your expectations around delivery times, snagging, and future support before you hire them. Maybe do it again, even if you have worked with them.

If they seem confident, make sure your requirements are as clear as possible to minimize back and forth, and to preserve lead times. Are they proven experts in fuel pricing software? If you can speak to historical clients for feedback first, it may give you extra confidence.

Can your internal resources maintain the platform?

Another plus point; ongoing maintenance of your in-house pricing platform should be convenient and potentially cost-effective. But have you checked that your internal resources will have the scope to manage this effectively? How do you evolve your pricing capabilities?

There’s no point having your own product if it generates too much support. You need to consider support in two ways; keeping the application running and the pricing capabilities.

If you’re in a dynamic market you’ll need to evolve capability to maintain pace with your competitors. If you’re not continuously updating the capability and performance of the pricing platform, you’re falling behind and you may not know it until it’s too late.

If you’re not sure, speak to your IT staff and, if applicable, ask them to discuss this with the software developer. Perhaps ask them to consider what other projects are in the pipeline to make sure your pricing platform can be given the priority it requires.

How high is your IT staff turnover?

The ongoing success of your pricing platform hinges on valuable input from the internal IT talent that were part of the development, build, and rollout process.

But if your IT department has a high staff turnover, there’s a good chance the key people involved will no longer be available down the line. These staff changes are unforeseeable, of course, but it might be a good idea to include in-depth training as part of any handover or succession plan.

To make sure core functionality is not damaged over time, it’s advisable to document these processes as thoroughly as possible.

How will you interpret the insights?

Introducing AI into your processes can address a growing list of business challenges, and fuel pricing agility is no exception. With accessible tech easily available, it’s possible to deploy a generic AI engine quickly and cost-effectively. However, have you considered whether your company has the technical expertise to get the most from a generic AI approach?

Do your developers have the skills to fully interpret the outputs? The devil is in the details, after all. Businesses simply cannot expect detailed levels of understanding, and strong fitness-for-purpose by applying a generic engine to a very industry and process-specific business question. Certain output variants of AI, such as neural networks, are notoriously difficult to interpret; by definition there’s no logic in the methodology used. This is particularly problematic with fuel pricing.

How do you understand which specific parameters are driving or influencing outcomes, or how important they are among all the other potential drivers? If your IT department lacks these key data analysis skills, it may be worth considering a specialist AI approach.

Ultimately, developing and creating a platform that delivers competitive fuel pricing requires a breadth of knowledge about your sites, fuel pricing across geographic areas, market trends, and your competitors’ strategies. You probably do have this expertise internally, but do you have the required technical know-how to develop an agile, flexible platform that makes the most of next-generation tech, too?

If you’re concerned about an external software developer having both these core competencies, it may be worth considering buying a platform instead. Check out part two to assess the pros and cons of an off-the-shelf pricing platform over a built platform.