Build vs. Buy in Mining Part 2: Thinking for the Long-Term

By building a bespoke software solution, you may think it’s cheaper and that it’s within your control. But how does this really compare with commercial ‘off-the-shelf’ software in the long run?

Keeping Your Solution Up To Date

Consulting firms are traditionally diverse in their services, not specializing deeply in any specific field.  In many ways, this is used to their own advantage, as it enables them to transfer their people across multiple industries and disciplines. 

This approach is quickly called into question in the Mining industry where challenges such as ore-body variability require detailed knowledge of the mining process coupled with the rapid adaptability of software solutions designed to optimize extraction and processing. 

Added to this, in the Artificial Intelligence (AI) domain, their focus has usually been on delivering one-off, custom-built software solutions. There has typically been very little thought given to ongoing ownership. Specifically, the upgrading and updating of these custom-built solutions on a continuous basis such that they keep pace with changing business requirements and technology advances. 

Imagine the logistics and cost behind such a service, each one of their clients with their own unique solution will need their own individual update. Now imagine keeping this going on, let’s say, a regular 3 or 6-monthly interval.

Here are some key considerations for your software solution’s long-term sustainability.

Build vs buy considerations:

  • How will your custom solution compare with up-to-date commercial software in 1,2 or 3 years’ time and beyond?
  • During the lengthy development cycle itself, how many weeks and months will you lose, where your operation could have already been working at the optimal state with the use of pre-built software?
  • What will the ongoing software upgrade process look like, how long will it take and how will you ensure its success?
  • In the case of AI, how long will it take to train the models with the models having no previous experience and limited access to data and diverse operating conditions?

It is forgivable to think that comparable effort goes into a custom solution and a commercial ‘off-the-shelf’ solution. 

This is a common misconception that is somewhat addressed with the below example of a ‘SaaS Iceberg’ that shows the effort that goes into a commercial ‘off-the-shelf’ software solution. Years upon years of development and refinement by experts in every relevant field go into building these solutions. The minimal weeks of on-site implementation that you witness are only the tip of this proverbial software iceberg.

The Cost of Misaligned Expectations

You have decided to build your solution. You’ve registered a project, it has been approved. Your chosen consulting firm has the purchase order, and the project kicks off. 

Two months in, there is scope creep despite capturing technical requirements diligently. Several unexpected issues occurred during the data validation process. You will require more complex models due to factors overlooked during the initial assessment of requirements. It is a capital project; thus, it delays the full implementation due to the approval process. 

You finally released the product after many months of delays and lost opportunities. One problem, the delivered product varies in a few areas, and you realize that expectations were misaligned from day one. How does this affect your operation after many months or years of development costs?

It’s sadly an all too familiar scenario, according to an article by Forbes, Project Management Institute (PMI) found that 43% of custom-built IT projects exceed their initial budgets, 49% are late, and 14% fail altogether.

The Subscription Economy

The disruptive nature of licensing models in all aspects of our lives is the reason for SaaS (Software as a Service) seeing such monumental uptake in pretty much every industry. The reasons are compelling, not least because customers remain in total control of the relationship with the option of ending the subscription should they be so inclined.

SaaS AI providers need to focus on delivering continuous innovation to their software and models through regular upgrades to make the proposition even more compelling and ‘sticky.’ 

As a result, the SaaS pricing model has driven a complete reverse of software projects and the old model of expensive on-premise, perpetual software licenses.

Because this is a SaaS provider’s core focus, the emphasis will be to keep a solution at the cutting edge at all times, providing a cost-effective approach to software deployments with a greatly increased chance of success.

If you are in a position where you need to decide on whether to build or buy, we have a comprehensive whitepaper on the topic. You can click on the button below to download your copy.

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