I've worked in many analytics projects across a number of companies as a consultant. I'm a big believer in "decision support systems". Find out what decisions your customers need to make, repeatedly, to their job. Quantify the heuristics and visualize that information (and that information only) in an easy to consume manner. More often than not that's an email or PDF. Another advantage is that by supporting the business users they feel less threatened by the changes or technology.
I think "self-serve" analytics is silly, the idea that you put all of the data in front of people and they'll derive "insights". That's not how normal people or data work. We just had a discussion on HN the other day about Facebook's Prophet, and its pitfalls. Meanwhile we expect Joe in sales to be able to identify useful trends on a chart he made. Every company needs to forecast, regardless of their sophistication. That stuff needs to be defined by the right people and given to the users.
I helped build the analytics group at a PE fund, and this really fits with my experience.
Good decision support is where most of the value is, and it’s about building things that draw conclusions, not just throwing the data over the fence with 50 filters and expecting the end consumer to do the actual analysis.
I now work on an open source, code-based BI tool called Evidence, which incorporates a lot of these ideas, and might be of interest to people in this thread.
Agree with both of you, and would add that knowing who is using the system, and what they need to get out of it is really the key to making them shine.
Too many systems have too much data for too many customer categories and end up being useless to everybody.
This is it, really. I remember back during a previous section of my career when I was running BI for a manufacturing company. We were asked to web-ify some legacy reports that either ran on desktops using Access & Excel or were on older BI products (Cognos). It was shocking -- at the time (I was naive) -- how many business requirements were essentially "replicate Excel in a browser", and completely divorced from the actual business processes and decisions that needed to be made.
Also, it might surprise a lot of less experienced developers just how many reporting tools are actually pieces of a workflow, not just reports. If you sniff this out during the requirements phase, do your best to convert these reports into features of an actual workflow app/system rather than allow them to persist as standalone reports.
>either ran on desktops using Access & Excel or were on older BI products (Cognos). It was shocking -- at the time (I was naive)
I think some people have a skewed view if they do most of their work with VC funded/SV companies. The average person at these companies is way more data savvy than average.
But there are so many companies out there that make a ton of money and have data-unsophisticated-but-domain-wise users, and old systems. Low hanging fruit.
I agree that the term "self-service analytics" (especially the 'analytics' part) and "insights" just passes the wrong image of the real need of business users out there. It mixes 'strategic insights' with 'operational needs'. And I think self-service needs to be about operationalizing data. Sales managers are not necessarily looking to 'analyze' data or 'get an insight'. They need answers from data to manage their team. They need to track well-defined KPIs. See how their salespeople are doing and be able to have a productive meeting to tell them what they are neglecting. Customer success people need to "pull some data real quick" on the usage of the product by a certain client before a meeting.
These things happen all the time. And yet most companies out there think that the solution is to just build a bunch of dashboards, foreseeing what everyone will ask in the future. And then nobody checks the dashboards. Or finds the right one. And then they have a team of SQL translators pulling data for ad-hoc questions. That's silly IMO.
I'm obviously biased as a founder of a self-service analytics company based on AI (https://www.veezoo.com). But this is just my 2 cents on a topic I really care about.
> I think "self-serve" analytics is silly, the idea that you put all of the data in front of people and they'll derive "insights".
In my experience, what "self-serve" really means is "non-developer". The end user won't build it, they'll have a BA do it. But it does mean they don't need IT to help.
Have you ever had a decision maker who struggles to articulate what business decisions they want to improve? How do you handle that?
I’ve heard pretty high-level managers respond to that question with things like “we were hoping your data would tell us” in response and I’m not sure what to make of it.
>Have you ever had a decision maker who struggles to articulate what business decisions they want to improve? How do you handle that?
Hah, 90% of the time. I think a big part at being good at this job is being able to coerce that information from people.
You need a process of drilling down, kind of like the 5 Whys[0]. You want to make more profits, right? That means we need to either increase revenues or decrease costs. Are we measuring all these things (you'd be surprised at the number of seemingly successful companies who can't)? Okay, how do we affect revenue? By increasing the number of users or increasing the revenue per user. Are we measuring those things? And on and on. It's a perfect way to iterate, and as the company matures it can be infinitely more and more sophisticated. For lower level people, sometimes it means sitting there and watching them do their job.
This is the right mindset for sure. Most of the time the initial question is very loosely defined, but actually having these conversations with the people who "want data", and helping them structure their thinking is also a hugely rewarding part of working in data and analytics, and will help you advance in your career.
It can be easy to have a cynical view of what people are asking for, but in my experience there is often real value you can uncover.
One thing which helped me a lot is having a decent understanding of accounting and finance. A fun, and fairly quick, way to develop that is by taking a course on financial modelling (in excel). Modelling a business in a spreadsheet is a lot of fun, and it helps you build good intuition on the underlying "physics" of how a business makes money.
My most successful projects were sending scheduled emails for things found in a cluttered dashboard (or tucked behind a few filters). Happiest customers, most repeat business and biggest impact.
> I think "self-serve" analytics is silly, the idea that you put all of the data in front of people and they'll derive "insights". That's not how normal people or data work
So well said. It doesn't shock me anymore when someone asks for a succinct summary or a PDF version rather than digging through dashboards on their own. In my company, we have a user-facing analytics product, and we added the option to take a PDF snapshot on a recurring basis and send it via email!
The grander your title, the more likely you are to want a succinct summary of need-to-know data delivered to you in a convenient format. For most executives, something in their email is best; they are there anyway, no logging in to anything.
I think "self-serve" analytics is silly, the idea that you put all of the data in front of people and they'll derive "insights". That's not how normal people or data work. We just had a discussion on HN the other day about Facebook's Prophet, and its pitfalls. Meanwhile we expect Joe in sales to be able to identify useful trends on a chart he made. Every company needs to forecast, regardless of their sophistication. That stuff needs to be defined by the right people and given to the users.