Farhan C.

The best analytics leaders I've worked with are masters of managing up. They keep executives informed while shielding their teams from distractions. A valuable skill to learn.

19

2 Comments

"Data is a precious thing and will last longer than the systems themselves." — Tim Berners-Lee In the data and analytics space, we often focus on the latest tools and technologies. However, the true value lies in the data itself and the insights we can extract from it. As professionals in this field, we must bridge the gap between technical innovation and business impact. Let’s continue to push the boundaries of what’s possible, but never lose sight of the business problems we aim to solve. Our work should always translate into actionable insights and tangible results. To business leaders and other professional across organisations, embrace the power of data-driven decision-making. Invest in understanding the potential of analytics and data science to transform your strategies and operations. Collaboration between technical and business teams is crucial for harnessing the full potential of our data assets. Together, just like my team at Turner & Townsend and I, let’s build a future where data not only unlocks some progress but creates lasting value. How are you leveraging data to make a difference today? #DataScience #Analytics #Leadership #BusinessIntelligence #DataDriven

32

1 Comment

I was yakking about propensity models last week and I found a great image to highlight how it works. This is a great way to use machine learning to uncover hidden patterns in your customer base and identify a priority list. Segment your userbase and train models based on the outcomes they've been through in order to purchase or not purchase something from you. BigQuery is a great choice for initially getting the data, I export it into a Python notebook inside the query editor and do all my cleaning and training there. A Neural Network will easily be able to uncover patterns and they are easy enough to train and get some good insights from. In the case I presented last week I used A XGBoost Decision Tree to train and uncover the patterns in users. I'll be using TensorFlow for my next model when segmenting, I think this will yield much better results. Supercharge your marketing or lead distribution with propensity models! #tensorflow #machinelearning #digitalmarketing #bigquery Credit: Antoine Aubay https://lnkd.in/deZwXsv9

1

There are so many data and analytics podcasts! But are there any "missing" topics? I get the honor of serving as host of the Mining Your Own Business podcast, and I've gotten to interview some great minds in analytics. As we venture into our 3rd year of the podcast, I'd love to cover topics that folks find the most interesting. So is there anything that is currently missing from the podcast lineup in the data world? Feel free to share your favorite podcasts as well, always looking for inspiration! (This isn't meant as a setup for you to say "MORE DATA COMEDY!!", but I won't be angry if that's what the people want) #datascience #analytics #podcast

8

3 Comments

Do you speak data? The ability to be data literate is critical for everyone to progress in their career. Gartner reports that 82% of business leaders expect all of their employees to be data literate. That is why I was excited to speak on this topic to Best Buy's Emerging Careers ERG. Data Literacy is usually defined as “the ability to read, write and communicate data in context." It was exciting to experience the energy and enthusiasm of almost 200 young professionals eager to learn. Too often people misuse data by taking it out of context (if you are looking for an example listen to most politicians) - and I am hopeful that these future leaders at Best Buy will help transform our culture to making data-driven decisions. Data is often hyped as the "new fuel" or the "new currency" - but it is worthless if everyone does not know how to speak the same language. Thanks to Soren and the group for inviting me in. How are you helping your company speak the language of data? #dataliteracy #bestbuy #cdo #datafluency #datagovernance #cdo

53

6 Comments

When managing data teams, I didn't love weekly 30 minute 1:1's with my reports. I preferred to do a 1:1 every two weeks. Generally 1 hour, sometimes 30 minutes, depending on the person / their role. The weekly meetings turned into tactical status updates that could have been emails. I found doing a 1:1 every two weeks let us cover meatier topics in more depth. I trusted my team to handle their work independently week-to-week. And you should be talking outside meetings :) It slows things down when, instead of sending a quick note, people wait two or three days until their next 1:1. Thought I'd share since there have been a lot of articles floating around about how the Nvidia CEO doesn't do 1:1's. If you don't love standard 1:1's, there are things you can do besides just getting rid of the meeting. I think it's important that people get some dedicated time with their managers. It really depends on your team (the 1:1 is more for their benefit than yours) but try mixing things up!

88

17 Comments

In two weeks, summer vacations will be over, 2025 planning will begin, and data leaders will start being told they need to "do more with less" next year... There are three ways you can make this work: 1) Pile on more work and burn out your team 2) Help your existing team be better data people 3) Be more focused on work that makes a larger business impact Method one will work for a quarter, but then quality will plummet, your best people will leave, and your team will be stuck in a very bad place. Crunch time is fine temporarily but it can't be a permanent state. Method two is always a good decision, but companies criminally underinvest in this. It's not even a matter of money - developing people is extremely cheap compared to everything else we spend money on to get business results from data. It's mostly a matter of not having good external options, and managers not having enough hours in the day to get deep into the weeds with everyone. This is one of the big reasons I made the Top Data Person professional development program. I thought there should be a place for senior and mid-level data people to hone the craft of being "highly effective at driving undeniable business impact with data." (besides not performing up to their potential, and spending decades making avoidable mistakes in a process that is painful both to them and their companies 😂 ) Route three is very important from the data leadership side. You need to be effective in setting ambitious but realistic goals for your team that will drive the business impact you need. This is where you see a huge difference between effective vs. ineffective leaders. Ineffective leaders "lose the season in the draft" and set their teams up for failure before the year even starts. Good leaders set realistic expectations for their teams that are focused on the highest priority business outcomes. The best leaders set high expectations focused on business outcomes, and also have built teams that can live up to those high expectations and occasionally blow them out of the water. Anyways, good luck for next year! I'd ask some data leaders to share how they approach "needing to do more with less" but there are some questions that have too much scar tissue to be able to answer in just a few words 🤣

16

8 Comments