You've heard of last mile logistics but what is the last mile of data analysis? In the following post we explain last mile analysis, provide examples, and list some common tools. Continue reading or use the table of contents to jump to a specific section.
- What is the last mile problem?
- What is the last mile in analytics?
- What's the difference between last mile tools and business intelligence (BI) tools?
- What are examples of last mile analysis?
- What are last mile analytics tools?
- How did we get to the last mile problem in analytics?
- Why is Row Zero the ideal last mile analytics tool?
- Conclusion
What is the last mile problem?
The ‘last mile’ problem refers to the challenge of getting products from distribution centers to the end consumer’s doors. Originally coined by telecom companies, the term ‘last mile’ gained popularity with companies like Amazon distributing products to customers’ homes. Going from the last hub in the distribution network to the final point of delivery ends up being the most expensive and challenging part of the distribution network.
What is the last mile in analytics?
Last mile analytics refers to the last phase of data analysis journey that takes an insight and translates it into specific activities that produce real business value. What does this look like in practice? Typically, data teams share analyses and dashboards with business teams. The business teams digest the data, asking questions and ensuring they understand it. Once business teams internalize the results there are automated or manual steps to realize the value identified by the insight, like saving money, increasing revenue, reducing churn, or driving any other business initiatives. The last mile is the gap between the insight in the dashboard and the ultimate value a business can realize from it.
What is the difference between last mile tools and business intelligence tools?
BI tools are generally great for implementing dashboards, beautiful visualizations, and pivot table style analyses. Popular BI tools are Tableau, PowerBI, Looker, and Metabase but there are many BI offerings. Companies use BI tools to monitor performance metrics for various departments and business initiatives or perform specific analyses on large data sets. Data, analytics, and BI teams are the core creators of analyses in BI tools. Business teams typically consume BI dashboards as viewers. This separation of responsibilities creates an inherent disconnect between data analysis and business action.
Last mile analytics tools are the products business teams actually use to identify, analyze, and modify, and model data, that enact changes to the business. Today businesses use a combination of purpose built tools and spreadsheets for activities like supply/demand planning, financial planning and analysis, capacity planning, product analysis, revOps, and pricing, among a myriad of others. Insights from BI tools drive subsequent activity in last mile tools. Are sales of a specific product trending down? Dive into the row-level data to figure out if it is out of stock, mis-priced, or getting bad reviews. Is an enterprise customer up for renewal? Filter and sort usage data to determine how many new licenses they need. What is the cost savings of a new project? Pull historical data and model costs with a new project in place.
What are examples of last mile analysis?
Finance
- Financial planning and analysis
- Performance reporting
- Revenue Recognition
- Internal audit
- Pricing models
Operations
- Demand and supply planning
- Capacity planning, hosting/production capacity
Product analytics
- Cohort and trend analysis
RevOps analysis
- Payment health analysis
- Attribution models
- Pre-sales performance analyses
Ad-hoc analyses
What are last mile analytics tools?
Last mile tools are those used by business teams to take action on a data insight. These tools are sometimes automated and other times manual. An automated last mile tool would identify likely to churn customers and automatically send them an offer or email to try and prevent the churn. A manual tool is one that enables a business user to drill down into big data sets and identify the root cause of lost revenue, higher return rates, or customer segments. Below is a list of some last mile tools.
Generic Tools
- Excel
- Google Sheets
FP&A tools, financial models
- Datarails
- Workday
- Mosaic
Demand/supply planning tools
- Oracle Fusion Cloud
- Anaplan
- Avercast
- Logility
Pricing models
- PROS
- Prisync
Product Analytics
- Amplitude
- Mixpanel
- RevOps
- Gong
- Clari
How did we get to the last mile problem in analytics?
When computers were nascent, spreadsheets ruled the world of data analysis. The flexibility of a spreadsheet and lack of purpose-built analytics products meant spreadsheets were used to perform every type of analysis. Business intelligence (BI) tools were developed when the power of big data was becoming apparent and data set sizes were outgrowing the capabilities of spreadsheets, which currently can only open 1 million row data sets. Control of data was put in the hands of analytics and BI teams who mastered SQL, Python and a number of big data and BI tools.
Since that time BI tools have continued adding features, fancy visualizations, and more complex filtering in an attempt to fulfill the promise of self-serve analytics for everyone in an organization. In addition to BI tools, a myriad of purpose-built and vertical specific analytics solutions have sprung up to offer pre-built solutions to manage big data sets for every analytic need.
Despite the efforts of BI tools and purpose-built solutions, it is all too common for a data analyst to produce a dashboard only for their business partner to ask “how can I get this data into a spreadsheet?” Conversely, BI and analytics professionals get bogged down with long lists of requests for different slices of data. In an effort to prevent mistakes and pre-build an analysis, BI and analytics tools have become too rigid and complex, making it difficult for business users to learn and pushing them back to the spreadsheet where they are more comfortable. Spreadsheets available to business teams are under-powered for modern data set sizes and lack connectivity to data warehouses where the cleaned and curated data is stored. When confronted with an ad-hoc analysis of a big data set, business teams are forced to cobble together an analysis with any number of tools and workarounds to fit the data in a spreadsheet and characterize it. Spreadsheets are also frowned upon because they run locally and perpetuate exporting data from secure repositories to the uncontrolled world of local storage. They aren’t built for modern enterprise analytics needs. Thus the data and analytics world has been transitioning away from spreadsheets for the past 20 years.
Why is Row Zero the ideal last mile analytics tool?
Row Zero was designed to be an enterprise grade last mile analytics product that gives users the spreadsheet experience they are comfortable with and the power they need. With the ability to open 1 billion row data sets, run and store data safely in the cloud, connect directly to data warehouses, and share across teams, Row Zero is the last mile analytics tool business teams need.
Instead of forcing business teams to learn complex and rigid BI tools, Row Zero enables them to work in the UI they already prefer. When business users have self-service solutions that empower them to conduct their own analyses on curated data with established metrics, they will inherently trust the insights more, leading to a bias for action. Eliminate the need for accounting teams to split their data across multiple Excel files and stop forcing finance teams to work with rigid FP&A products that force a specific workflow. With Row Zero, these use cases are easily facilitated by running queries that pull data into Row Zero where an analysis can be completed, stored, and automatically refreshed as new data comes in. Row Zero is the modern spreadsheet that supports all your last mile analytics needs.
Conclusion
The last mile in analytics is the gap between the insight gleaned from a dashboard and actual business value. The last mile gap, when properly executed, can yield real value. However, when the last mile gap is not properly resourced, returns on data investments are never realized. Today the last mile of data analysis is filled with Excel spreadsheets or rigid and complicated purpose built tools. Row Zero is an enterprise grade last mile analytics tool giving business teams the spreadsheet UI they are comfortable with and the power of BI tools.