Build or buy – the age-old question that seemingly has no clear answer, whether you are a diligent consumer or an enterprise decision maker.
Consider these scenarios. A homeowner imagines that a backyard shed would satisfy their need for additional storage and working space for personal projects. But, would the homeowner ultimately save money by building it themselves exactly to their own specifications? Or would the modular, prefabricated storage unit offered by the local home goods retailer suffice and be a more economical buy in the long term?
In the case of the conscientious do-it-yourselfer, he would need to consider the cost to purchase a set of building plans, factor in time spent with the local zoning board to get the plans approved and obtain the building permit, purchase the building materials and have them delivered to the home, and actually perform the construction. Other considerations would be whether they have the tools and skills to safely perform the construction and whether the building time would take them away from other important projects or family events. Alternatively, the homeowner would weigh the cost of the pre-built shed and consider the associated landscaping preparation required, delivery, and installation costs involved. Either way, it would be nice for the homeowner to be able to use a simple ROI equation that would clarify the decision.
At another level, commercial organizations of all size regularly struggle with similar build versus buy decisions. Consider the Fortune 500 company that needs to decide whether to develop their own ERP system or purchase one off the shelf from one of the many reputable vendors in the market. The critical decision-making factors are not dissimilar to the DYI homeowner. In the long run, will it be less expensive to build with internal resources or buy the software? What is the expected short- and long-term ROI? Does the company have the skills and resources to build the application efficiently in house in the necessary timeframe? Is the solution scaleable to the needs of the future? Again, similar questions, more intangibles to consider, and few logical equations and algorithms to help guide the decision.
The same make vs. buy question is faced by our own customers who require solutions to the many challenges they need to address to protect and license their software. For example, software piracy and ineffective licensing have a direct financial impact for businesses: Unauthorized copies and unlicensed use mean significant losses in revenue, while poorly enforced licenses can mean lost revenues and lost control. Additionally, protecting intellectual property is paramount, not least to secure one’s financial integrity and ability to keep innovating. Without adequate protections, creative ideas and other intellectual assets are at risk of theft, emulation, and unauthorized use.
Today’s digital transformations across all sectors of industry have put software security in the spotlight, in particular, the means to prevent nefarious manipulation and cyberattacks. In practice, protecting software against manipulation and tampering calls for security technology on various levels, from encrypting and signing code to more advanced techniques for recognizing and averting attacks.
Furthermore, businesses are facing increasing pressure to respond to changes in consumer expectations, such as having the ability to choose licensing options including subscriptions, pay-per-use, or other modern alternatives. This requires new strategic thinking on the developer’s part and a flexible licensing system that enables them to address dynamic market changes.
So, while the need for a software protection and flexible licensing system is clear to many, the make or buy approach is still somewhat muddy, as we experienced with our current customers who opted for the buy approach to our CodeMeter licensing and protection system.
To help our future customers make their decision, we engaged in a comprehensive analysis to determine the cost of purchasing, implementing, and maintaining our CodeMeter system in action and the subsequent short- and long-term Return on Investment. To make the calculations, we engaged in extensive interviews with leading executives of four companies using CodeMeter. We organized the available data into distinct scenarios so the calculations would offer meaningful insights into a range of use cases and sectors of industry and size company.
The ROI was then determined by taking the initial investment, the licensing costs during active operations, the potential revenue growth, and the expected savings into consideration to get a clear impression of how the solution would impact the user’s profitability. The calculation was made over a three-year timeframe to offer a meaningful impression of the long-term effect of opting for the CodeMeter licensing solution.
While not surprised, we were pleased to be able to show definitively that each customer benefited from adopting an efficient and flexible licensing system. In each case, CodeMeter not only improved their profitability, but also sharpened their competitive edge, protected their IP, and provided a predictable model for long term growth.
But the story doesn’t end here. We now have an objective and demonstrable ROI model that we can share with our future customers to help them with their important decision to either build a homegrown software licensing system or purchase a proven, automated licensing and protection system like CodeMeter. If you are interested in learning more about our CodeMeter ROI methodology and calculations, I invite you to download the Whitepaper, The Commercial Case for CodeMeter: Insights from Customer Case Studies.
