This site uses different types of cookies, including analytics and functional cookies (its own and from other sites). To change your cookie settings or find out more, click here. If you continue browsing our website, you accept these cookies.
Announcing Alteryx + Snowflake | Alteryx and Snowflake make analytics and data science fundamentally easier. With the new integrated starter kit, you can push down data prep transformations and more into Snowflake for faster data quality and analytics output. Learn More
Director - Financial Planning & Analysis; Analytics Consultant
Overview of Use Case
Iron Mountain is a global leader in records and information management. Their financial planning and analysis team is using location intelligence to identify facility storage capacity and driving storage usage through pipeline demand data from Salesforce. Discover in this use case how Alteryx empowered the Iron Mountain team to create a suite of commercial, financial, and real estate reports that facilitate proactive decision-making across the business. Because of these changes, now 80% of CEOs and regional managing directors and 100% of the regional support actively check the reports each month. The results couldn’t be any different: they are above their sales target at 109%!
Describe the business challenge or problem you needed to solve
Iron Mountain build and rent safe and secure storage warehouses with racking solutions to store and manage the critical assets of their customers, including secure destruction. They need to fill up their warehouses as quickly as possible. Once those spaces start to get full they invest in the metal racking to store the boxes. And when it gets three quarters full, that's when they start to make a profit in a warehouse.
They make large investments up front which take some time to pay off. There is a strong need for analytics to back up those crucial decisions. For commercial, they need to win customers and bring in new boxes, so it’s fundamental to know if salespeople are selling well, if there is a market, if they can improve win rates, etc. In the real estate field, they need to answer questions like how full each warehouse is? And their finance department needs to know what are the most profitable products and countries, they need early indicatiors when something is going wrong or where there is opportunity to do even better.
They need to answer a lot of questions and Salesforce reporting in Excel was no fun. It was showing just a point in time and they coudn’t know what the pipeline was six weeks ago, 12 weeks ago or a year ago. They needed to capture historic pipeline trends and build better reports. Trying to figure out a better solution, Matt Semple downloaded Alteryx trial and he hasn’t looked back since then.
Describe your working solution
The Salesforce connector in Alteryx Designer was essencial to easily bring in all the data they needed, about 10 millions records. To get the five key sales metrics, they started working with an Alteryx Partner, Interworks ,who helped them build the workflows to get the insights they needed.
COMMERCIAL PERFORMANCE INSIGHTS:
DEMAND GENERATION - Growth in sales pipeline over previous 1, 13, 52 weeks
PIPELINE COVERAGE - Current pipeline size measured against annual sales target
PIPELINE HEALTH - Age of sales opportunities & velocity through sales stages
WIN CONVERSION - Overall win rates & close rates from each sales stage
SALES FORECASTING - Full year projections based on latest pipeline & close rates
Now for each opportunity on Salesforce they have a track of it through the whole process. So, they have the timeline of each opportunity of each point of the process. This means that they can calculate the likelihood of a close at each stage of the business. Below is the workflow showing how to go from the close rates of each of the salespersons to the aggregate country average rate.
Step 1: filter to the relevant Stage Data, so that's saying "I just want Stage 1."
Step 2: a simple table calculation that says “if Stage 1 is true, take the value, and if it's not, I don't want the value in that case,” and then that’s the won quantity.
Step 3: aggregate to the salesperson level.
Step 4: it provides the close rate for each salesperson.
This model is very simple and the output of is a weekly updated dashboard that goes into Tableau's BI visualization tool.
GROUPING DATA BY LOCATION
Iron Mountain has 1,500 storage facilities located throughout the world. They needed to know if they have capacity in the right locations to meet client’s storage requirements and to ensure utilization of all facilities is high, to maximize investment returns. Also, those insights are crucial to determine where to grow or rationalise their real estate portfolio. They used Google Maps API and Alteryx Spatial Tools to group storage facilities based on where they are located in the world.
Use the Google API connector to file coordinates of facilities
Step 1: Plug in the latitude and longitude into it to get a
Step 2: Pick radius size. It'll give you something like in the image below. The red dots are the centroid, that's the individual facility, and the green circles is the radius around it. There'sclearlyna overlapandthere'sclearlyareasontogroupthesetogether.
Step 3: To see which ones are grouping together they used the spatial match tool. Usually, you have two different data sources, you'd want to join one on the other one, but in this case they joined it on each other to see which ones are together. There's going to be some issues with that, like duplicates, because it's going to join on its own facility, and there's going to be a two-way correlation. Then, you add a filter tool to basically say “if thefacilitynumbersarethesame getridof”
Step 4: There is also a rule if the country isn't the same, because there's some instance where facilities could be in different countries but overlap. So, Bratislava and Vienna, they're very close to each other and there's a few facilities around there, and but they just want to make sure they don't overlap.
Use Alteryx Spatial Tools to Group Facilities in a 10 Mile radius
With their analytics solution now they know their real estate capacity status by facility and market. They know where new commercial opportunities exist and have an algorithmic prediction of how much they are likely to win and when.
The end product: a dashboard with capacity and utilization rate
Describe the benefits you have achieved
When Iron Mountain started publishing their dashboards they had very low expectation that people would actually check them, maybe they would get 50% of participation. But when they mesasure the participation they were staggered. About 80% of CEOs and regional managing directors were logging in each month. To get 100% of the Regional Support team shows that this is now the go-to source for commercial data.
End user dashboard active participation rates
“In terms of our sales performance this year, the dashboards aren't completely driving the sales performer, I can't take credit that we've caused that sales success, but there is a correlation that we've now got tools, everyone's looking at sales performance, everyone's driving sales team to close the deals that are furthest down in the pipeline. We're above 100%, we're 109%,” said David Turley.
Current Commercial Performance
The entire PowerPoint presentation can be found here.