Will you Build or Buy? one of the most common and challenging dilemmas facing managers looking at technological optimization in mining today.
A stack of variables and considerations lay in front of you, and the stakes are high. In this series of posts we will be addressing the most common challenges, and hopefully, help to clear the mist a little. Today we’ll look at the cost considerations.
Making it Work…. or Not
Time to value – the time between your initial investment and the point upon which you will derive value from your solution for the first time is a major consideration to take into account as it relates directly to ROI and missed opportunities as a result of a project running late.
Intellisense.io is an AI Software as a Service or SaaS provider, and our Commercial Of The Shelf (COTS) Platform and apps are deployed within 2- 3 months. And this is the general trend with SaaS companies. In addition to a rapid Time to Value, our focus is on providing sustainable value over a long period to your operation with no upfront costs. You have access to immediate live functionality and computing infrastructure as soon as you subscribe to a SaaS solution. These agreements devoid you of a considerable amount of risk; a large amount of which lies with the SaaS provider, as long-term value delivery and the contract duration determine whether a SaaS provider is profitable or not.
In-house solutions may have the technology down, but still see inferior results without the same level of subject matter expertise unless the software falls directly into the business’s core competency.
Conversely, when a reputable consulting firm builds a software solution, ‘the bill is settled before the goods arrive’, paying for the initial buildout, platform migrations, upgrades, and bug fixes to name a few. Unforeseen costs also regularly pop up, both during the build process and after go-live.
According to a report by the Apigee Institute up to 27% of app deployments exceeded planned timelines. In addition, research by McKinsey indicates that 7% of Enterprize IT projects are late on delivery. Shockingly, neither of these statistics consider the 19% of projects considered failures and the 52% of projects that exceed budget and fall short of expectations and functionality – Standish Group’s 2015 CHAOS Report. The study indicates the project size can directly correlate to the likelihood of its failure.
It is well-known that technological advances are taking place in every industry faster than ever before. Now think about keeping up with Machine Learning trends as an example, you can see from the diagram above the complexity of a solution like this. Will your software builder and in-house IT team be able to keep you future-proof? To keep up with the trends, you need a business model that allows for continuous development, upgrades, and releases of your software. A major release every six months is the general trend for us at Intellisense.io, with multiple minor upgrades in between. Dedicated Data Scientists, Software Engineers, Cyber Security Specialists, Mining Industry Specialists, and Product Teams make sure that all the bases are covered on our clients’ behalf.
A significant cost to consider is thus the cost of falling behind on industry and technology trends if you are looking at a custom build project. SaaS providers constantly upgrade and maintain their software to provide you with up-to-date technology and value, allowing you to focus on your core profit-generating activities.
The quality of a custom software build will be of high value initially seeing as it is built specifically for your unique needs, but maintaining the custom-built AI solution once implementation is complete will be costly and complicated, and it will be your responsibility. It requires considerable refocusing of your capital and IP resources to activities and processes outside your core profit-generating operations.
Custom software builds require a high degree of client involvement in their custom AI solution. Very complex projects need in-depth scoping on a continuous basis from your perspective. Highly skilled human capital is required, such as metallurgists and geologists, to ensure relevance to your operation is maintained throughout the build. Most software builds fall behind schedule, with scope creep being the main reason. A common occurrence is the software being outdated by the time the project eventually reaches completion. How do you make up for the time, resources and money already invested in an outdated system?
Data is pivotal to accurate AI and ML models. With an in-house solution, once your AI system is deployed, members from your team need to analyze, on an ongoing basis, the outputs of your AI system to ensure data credibility and quality before deploying the data to training Machine Learning models, keeping those team members from their primary function.
SaaS software providers have expertise in software, data science, and mining – continuously undertaking data validation so that you can focus on mining. Critical members of the mining team are now free to concentrate on their roles and attain optimal value from AI solutions.
Continuous Business Improvement is a standard operating practice in mining operations and is an effective way to maintain maximum operational efficiency. Ongoing improvement projects using a linear execution method sometimes suffer from an inability to scale with sudden changes in your business and where knowledge gained on a particular process at a specific site is lost when the same problem occurs at a different site. The advantage of introducing real-time AI software through a SaaS provider into the business improvement process is that it enables the agility to scale and embed continuous optimization.
Thank you for reading our post. If you would like to read more about Build or Buy, please download our Build vs. Buy Whitepaper.