Build versus buy – an empirical approach (part 2)

DEVANG MEHTA
Thursday, December 3, 2015

In a PREVIOUS POST, we described a framework for evaluating the right inflection point for a ‘Build versus Buy’ scenario for implementing an IoT Analytics solution at your organization.

In this post, we will expand on this – first with a few numeric use cases based on our interaction with customers and prospects. As a reminder, we define Value of Risk = Cost of failure X Chance of failure.

Case 1: 8 Full-time Employees (FTEs), Chance of failure = 25%, Calculated Risk Value = $285K

Case 2: 4 Full-time Employees (FTEs), Chance of failure = 40%, Calculated Risk Value = $252K

Case 3: 8 Full-time Employees (FTEs), Chance of failure = 60%, Calculated Risk Value = $222K

Based on Glassbeam’s own internal experience building its Big Data analytics application, we can credibly state that a sufficiently comprehensive DIY Analytics Application will experience greater than normal development risks. Even though we believe the inherent risk is greater, we are confident that the reader will accept that the “Chance of Failure” percentages we assigned to each of the three example development teams are fair and reasonable.

 

Compared to the above costs for a DIY, we estimate that licensing a Glassbeam solution is significantly cheaper, faster to implement, requires minimal disruption in day-to-day activities.

The questions we hope this paper raises for the enterprise executive decision maker include:

  • Is the risk of building an in-house Big Data Analytics Application worth the investment when Glassbeam offers a time-tested and hugely scalable Big Data Analytics service that gets your company to realizing cost savings earlier?
  • Does the investment in the DIY Analytics Application distract from investing in your company’s core competencies?
  • Would you entertain meeting with Glassbeam to discuss, in greater detail, how the concept of the “build vs. buy” decision for Big Data Analytics directly applies to your company?

We encourage our reader to exercise the “Risk Value” equation using internal, measurable cost estimates. We then ask you to compare your calculated “Risk Value” to the alternative of investing that Risk Value in Glassbeam’s, industry proven Big Data Analytics Platform; an option that will decrease your go-to-market timing while generating measurable cost savings during year-one. We also welcome the opportunity to demonstrate how you can minimize opportunity cost and real costs by investing in the next best core competency option in parallel with investing your calculated “Risk Value” in Glassbeam’s analytics solution.