I play a game with my 12-year-old daughter on long road trips called “Would You Rather”. The premise of the game is simple, present your opponent with two undesirable scenarios and force them to choose the lesser of two evils. The fun is in making your opponent blush.
I ask her, “Would you rather have your Mom read the text messages on your phone, or see a picture of your BFF kissing your ex-boyfriend on Instagram?” Both are devastating. I am sure to win because it is an impossible choice and after a long pause she chooses Instagram on the logic that if her BFF is that disloyal she deserves to be matched with the lousy ex.
The human mind is a powerful pattern-recognition tool designed specifically to analyze and solve “Would You Rather” problems. Many of the challenges we face are “Would You Rather” problems with vexing, double bind consequences like “Would you rather pay more or wait longer for a quality result?”
We know intuitively that if we can identify a reliable pattern, we can create a formula to help us predict the probable outcome and then weigh the consequences to make a calculated choice. Predicting the probable outcome in advance based on a reliable pattern is the mark of cognitive maturation and is the basis of deliberate decision-making process. Predictive analysis gives us incredible foresight, which when coupled with effective action, gives us significant competitive advantage.
In a typical scenario, the translation will go through an entire supply chain series of “Would You Rather” decisions made by independent individuals. As inefficient as this sounds, the supply chain model actually is the best option for this type of work because it is flexible and scalable. Solving the complexity and inefficiency of the localization supply chain is a great opportunity to bring innovation. An efficient supply chain is the main value add of LSPs, so why aren’t we looking at this? Options:
1. Let everyone do whatever they want. Unfortunately, paying for every one’s unpredictable decisions with endless rework is the antithesis of good project management. This approach is a guaranteed way to frustrate and lose clients.
2. Don’t let anyone make any independent decisions—ever! The problem here is that we can’t really control the decisions of others and it is futile to try to make everyone else’s decisions for them. This option is a guaranteed way to frustrate and lose linguists.
3. Provide guidance on the decisions making. This requires advance planning to create specifications, quality guidelines and processes. Best practice includes style guides, glossaries, and issue escalation. Good project management is critical, but not enough. Good planning must be informed by good information ahead of time. This is where predictive analytics comes into play.
4. Provide visibility for every one of the decisions others are making in real-time and allow them to adjust as they go using predictive analytics. Consider the potential synergy of a team when they have visibility and can react in real-time. We need a way to predict the quality, capacity, and behavior of the team members regardless of the variables.
Enterprise Resource Planning (ERP) Solutions for Localization using Business Intelligence:
1. Resource Capacity Planning
2. Language Quality Management
3. Solutions for Onsite Interpretation
4. Future Applications – Telephone Interpretation, Segment Recommendations for Translators