How the IKEA Effect Drives Your Observability Pipeline

When my home office needed better storage, I made a trip to IKEA in Menlo Park. Standing in front of Galants, Bekants, and Hallans, I knew the shopping experience represented a fraction of my involvement with this furniture. Most of the effort would come later, as I shouted at instructions and searched for the right screw and hex wrench to assemble it all. When I finished hours later, I had a respectable office that I valued more because of the labor I put forth. 

This is called the IKEA effect, and it’s built on a bias called the endowment effect. The endowment effect basically says people are more likely to retain an object they own than acquire that same object when they do not own it. The IKEA effect takes this a bit further: people value things they created more than things they didn’t. 

The genesis of this story begins decades ago, but with cake mixes instead of assembled furniture. Originally called the Betty Crocker Effect, it began when General Mills replaced the dehydrated eggs in their cake mix with instructions to use fresh eggs. Instant cake mixes were too easy, the thinking went, and devalued the product because it didn’t require any labor. People felt they could get the same result by simply purchasing an already baked cake. Requiring fresh ingredients added labor, gave aspiring bakers the feeling they actually contributed to the baking, and that labor led to loving the creation. 

Unfortunately, love, as it often does, leads to irrationality. If you take this concept to the extreme, you’ll be milling your own flour before you know it. The challenge lies in striking the right balance between letting users add their own value with self-creation while avoiding getting them bogged down in needless details. 

At Cribl, we frequently hear from companies that attempted to build their own observability pipeline, and they’re bogged down in the details. Supporting multiple protocols, hundreds of different data formats, and a range of security and governance requirements is overwhelming. Building it on top of a mashup of open source tools makes the problem worse. The thing about the IKEA effect is this: it only works when the labor is successful. A half-assembled Havsta cabinet is as unsatisfying as a half-baked observability pipeline. 

We’ve taken the opposite approach with LogStream and our Packs feature. LogStream has always allowed users to assemble their own approaches to log routing, enrichment, redaction, and filtering with just enough DIY (but no coding required) to turn our customers into excited fans. With the addition of Packs, we open the LogStream functionality to application developers, operations teams, and SREs that want to build on top of the LogStream experience to further customize it. 

Packs can range from pre-built pipelines for reducing Windows XML Events, expansive enrichment of data as it flows through LogStream, or even new destinations leading to better data value. No hex wrenches required. 

The fastest way to get started with Cribl LogStream is to sign-up at Cribl.Cloud. You can process up to 1 TB of throughput per day at no cost. Sign-up and start using LogStream within a few minutes.

Evidence

• https://theconversation.com/the-ikea-effect-how-we-value-the-fruits-of-our-labour-over-instant-gratification-113647
• https://www.hbs.edu/ris/Publication%20Files/11-091.pdf