article thumbnail

Don’t Be Tyrannized by Old Metrics

Harvard Business

While effective metrics are essential for focusing attention and achieving results, they can also overpower better sense. Most industries cower to a few central metrics, the yardsticks that define the winners and losers. Metrics tried and proven over years become a guide to what’s important, driving resource allocation.

Metrics 70
article thumbnail

The Chief Project Officer: Roles and Responsibilities

Epicflow

Monitoring performance and benefits delivery The CPO is responsible for monitoring project performance, tracking key metrics, and ensuring adherence to project timelines, budgets, and quality standards. In addition, they also make sure that every project meets the established goals and delivers expected benefits.

Resources 221
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Great Digital Companies Build Great Recommendation Engines

Harvard Business

Recommendation engines (or recommenders ) force organizations to fundamentally rethink how to get greater value from their data while creating greater value for their customers. ”We didn’t think a recommendation engine was necessary at the time,” said one of the company’s web developers. Personalize offers?

article thumbnail

There Are Two Types of Performance — but Most Organizations Only Focus on One

Harvard Business

Every step of the process was measured, and real-time metrics were easily accessible. Similarly, when Starbucks baristas make your latte the same way across cafés, or when a software engineer delivers the expected features each sprint, you are witnessing tactical performance. Metrics emphasized speed.

Metrics 133
article thumbnail

The Kinds of Data Scientist

Harvard Business

These data scientists design, define, and implement metrics, run and interpret experiments, create dashboards, draw causal inferences, and generate recommendations from modeling and measurement. Data science for machines: here the consumers of the output are computers which consume data in the form of training data, models, and algorithms.

Data 132
article thumbnail

Scaling Customer Service as Your Startup Grows

Harvard Business

Don’t obsess over metrics like inquiry volume or time to close tickets. Don’t let your engineers hack together workarounds that will need to be maintained down the road; provide real engineering solutions to the types of problems new software has. What not to do. Don’t optimize for efficiency. What to do.

Metrics 129
article thumbnail

Uber and Other Tech Companies Could Make Simple Changes to Avoid Driving Away Their Female Engineers

Harvard Business

On February 19 former Uber employee Susan Fowler wrote an explosive blog post describing her time as an engineer at Uber. And it’s important to note that it isn’t only Uber that (allegedly) has a problem retaining and supporting female engineers. Her essay has received nationwide attention — and alarm.