Treat your data like a pizza.
Why is data like ordering a pizza?
To start with, no one wants to wait a long time for their pizza or for their data.
No one can agree exactly what they want. Is is ham and pineapple or month-over-month growth for the last two years.
Traditional is long gone. I’ll have a butternut squash with goat cheese and rocket pizza on a sourdough organic crust.
You might laugh at my anecdotal reference. Oh I work for an online food takeaway platform. I work in data I get it.
Just for some background. Before my current career in data, I worked multiple part time jobs paying my way through University. I spent some time travelling the world and during both these times I worked, yep, as a pizza cook.
I personally feel grateful to have worked in hospitality when I was younger. It’s given me an appreciation for this industry and how customer service plays a role in getting customers to come back.
I used to deliver pizzas to people. Long before smart phones and GPS maps. Armed with grid coordinates, a street directory (Refedex-yeah Brisvegas) and a torch to find the house numbers, I’d deliver orders of pizzas most nights during the week. Making sure hungry people got their pizzas delivery on time so they could enjoy them still steaming hot.
It was at a data event last year, talking to other people in my network, eating pizzas and sharing stories about difficult stakeholders when I jokingly made the connection.
Data is like delivering a pizza.
Think about it. You are handing the (hopefully) hot pizza (or insight) over to the customer. They are hungry and have paid extra for the service.
Think about the last time you had a bad takeaway. Have you ever gone back to the same restaurant and ordered again?
They want to know that what is in the box is exactly what they ordered. They don’t want to have to check it right then out on the street in the cold. They want to receive their product all in one piece. Not all squashed and soggy.
What they don’t want is someone leaving their pizza at the front door, or just tossing it at them, hoping they catch it.
And yet that’s exactly what some companies do with their data. Their business users place an order, the analyst prepares it and the just fires off an email to them with some data or some charts as an attachment. The equivalent of driving past their house and just frisbee the pizza box at the front door.
Why?
Time, pressure, volume of work, the normality of how data and information is delivered to the business. There are probably lots of other reasons, but not for this blog post to go into.
When I came to this realisation, I knew I had been guilty of this in the past. As analysts we were never really trained on this part. This “data handoff” to the customer.
When working for pizza companies it was one of the most critical parts of the training I received. Making sure you were professional, reading and confirming their orders, taking the pizza out of the heat bag and giving it to the customer without dropping it (I did drop some pizzas when rushing). Collecting the money and giving change.
It was the final stage of the assembly line. The last stage of delivering a product to a customer.
If you fail at this stage then the customer may not come back.
I’ve seen it at lots of companies where a chart was thrown together which lacked any sort of quality. As much as Microsoft Excel changed the game, it’s also helped create this complacency in how data is delivered. A selected data range, default wizard and a chart appears. We assume that chart is then fit for purpose because excel made it.
I’ve learned a lot in my current role, moving beyond just working with data, writing SQL and using Tableau to communicate this out. It’s what first opened the door to me in how data should be given to a stakeholder and why data visualisation plays such an important part in this process.
In the last few years, I’ve been working more strategically and have learned from some inspiring leaders, who can articulate a data vision and allow you to execute this.
Alberto Rey Villaverde introduced his simplified data model to me and the rest of the team at Just Eat. He used this term as a way to explain to the business how to get value from data.
Access, transform, deliver.
Access data by ingesting it from across the business into a centralised location.
Transform that data into usable components for analytical purposes.
Deliver that data to the business to unlock insight and value.
Delivering data. The last stage of the data assembly line.
As senior manager for data visualisation, my responsibility was the delivery component. Empowered by my manager, Stuart Knapp, I set about executing our vision for data delivery.
Handing it off to the customer, to make sure it was what they ordered, and that they were happy with the quality so they would come back again and reorder. Not just giving them some information, but also making sure the customer understood what they had ordered.
It’s also what the rest of the public and business see. They don’t see the people cooking the pizzas, or writing the code, extracting the data. They see the pizza delivery person out on the street, walking up to houses. They see the reports being sent out, being shared, charts being screen grabbed and sent in Slack or forwarded on in emails.
Being tasked with data delivery, I came to the realisation that there was another industry failure. We were treating all customers the same. Everyone had to get their data from the one reporting system.
Going back to the pizza analogy, this was so wrong!
In the pizza world we had so many different elements. Pre-orders, delivery, collection, VIPs, lots of different ways we could make sure our customers were happy and got what they wanted.
There was so much we could improve on when delivering data!
Data means different things, to different people.
By taking this customer centric view, I developed the concept called “data delivery spectrum” where at one end we had traditional data delivery via reports. Scheduled KPIs sent out to stakeholders.
Instead of trying to shoehorn 90% of work under “static reports” I opened up other components of the spectrum which covered interactive dashboards and data toolkits.
These data products allowed users to interrogate the information from the functionality built into the dashboard. Filters, parameters and other features which allowed the secondary questions to be answered.
I’m lucky to have a brilliant and passionate data visualisation manager in Mark Corbridge to deliver these products for me. He is also able to articulate this strategic vision which spews forth from my head. You can see more about our data toolkits in his talk at the Tableau 2019 Europe conference titled “From Tab-oh to Tab-Woah”.
Moving into the next component of the spectrum is Self service analytics. Controlled by data models and security, supported by data literacy and training programmes to show business users how to use the software that connects them to data. You can read some of my other blog posts about these training programmes and how I created them. It's one of the most effective ways to allow a large business access to the insight they need.
The final stages of the spectrum is to allow fully self service access, where access is granted to the database via SQL as per the analyst community, normally as part of a decentralised model within your organisation.
I shared this story as part of the Deloitte: Experience Analytics week, how our data delivery was supported by ThoughtSpot, allowing us to reach wide and diverse audience in data delivery. You can check out the video here.
The shift has been seen and recognised within the BI and Analytics space. Lots of software vendors are making these product changes to make data more accessible to these different audiences.
From Ask Data in Tableau, to ThoughtSpot — searching your data like you would Google, there are multiple ways you can expand how you deliver data to your business.
The value in treating your data delivery like a pizza, means you get to serve more customers, growing demand and keeping people satisfied.
Helping your business get value from data in order to make informed decisions. Now that's a tasty pizza!
