The Onboarding Experience

Every company strives to improve the customer experience to enable customer loyalty and sales. There are usually many points of contact with customers which means lots of opportunities to provide excellent service! Or if you consider Murphy’s law, lots of moving parts with a potential for problem points.

This project had strong achievements that helped demonstrate what is possible when you apply sound data practices and create an engaging dashboard.

The Results:

• Improved report processing and delivery times (from once every six months to daily)

• Improved engagement from end-users and leadership teams

• Improved customer success score (from 10% to 40% in under a year)

• Increased applications processed to drive more sales

• Reduced the effect of bottlenecks and worked towards eliminating them

• Improved data quality

• Celebrated wins across the teams!

This was one of several projects I was involved in that helped this team grow from a $100 million business to a $400 million business. There were many factors and players that contributed to this growth. Getting the data right was a huge component that drove the team to success.

The Situation

The leadership team had an objective: “We want to onboard clients within two days!” The idea of an onboarding program was a simple enough objective, one would think, but the leadership team didn’t even know where they stood on this metric! There was one report, delivered once every six months to the team. The bespoke software used didn’t provide any reports and getting changes to the application was very expensive and time-consuming.

Since this report was hardly available, the organization had no real oversight of what was happening and had nothing to act as a benchmark. We know there were several components to the process like time spent with the sales team, time spent with the risk team, time spent with the customer, and time spent at delivery.

Disclaimer: This is not a post to bash or put down any other tool or analyst. Excel is a very powerful tool in the right hands, and is readily available to the masses for a minimal cost! A lot of business intelligence solutions cost a lot of money which makes them inaccessible to everyone. I commend people for being able to achieve some cool things with the tools they have!

So what were the options? Here is how I addressed this.

The Approach

I made an assessment of the application used by engaging the end-users and analysts. There were lots of complaints from our end users about how difficult and time-consuming it was to use the application and our team of analysts were not keen on working with the data outputs. Everything was cumbersome and clunky. There was an ongoing investment to keep adding modules but not a lot to improve quality of life.

Next, I looked at the reporting available. Inside the application itself, there was a decent oversight of what’s in the system, but nothing that a high-level executive could consume or make sense of.

For this post, I have generated a simulated dataset that represents a similar situation so that I can build sample reports to demonstrate how having effective data visualization in reports can impact decisions.

The Old Report

Having a mission-critical report delivered just once every six months is not good. This is very reactive and doesn’t allow for effective change. By the time a decision is made, there is no way to see the impact and know if the decision made and the millions at stake are working or not.

Here is what the Excel report looked like:

Two pivot tables to form one report. These show the average time to decision and the first pass rate. Spot any trends or outliers?

These are two pivot tables on a single Excel sheet with filters for 2022. The filters are independent of each other and in the end, just wading through tables doesn’t provide much context to the situation.

To me, as an analyst and a stakeholder, there isn’t much I can derive from this and it isn’t exactly inspiring to dig through these numbers. Sure I have questions (and questions are a good thing) but not many...

• Where are we doing well? Where are we not? What are the causes?

• Are we on the right track? Is the performance satisfactory?

• What’s happening with September?

The New Report

Here is what the new report looks like:

Click on the image to see the live dashboard version on Tableau Public!

By using some modern tools we also have interactivity! The filters apply to every visual element on the dashboard and we even have tooltips!

A tooltip adds more context, or details, or insight. It definitely adds interactivity! This tooltip breaks down the performance for a particular month.

This dashboard answers the questions raised from the Excel version easily AND answers more, PLUS it asks more questions for us to investigate even further.

Previous questions:

• Are we doing well? The trend is moving upwards, so yes!

• Are we on the right track? There are visible improvements but it is stagnating. Maybe it’s time to look into what more we can do to keep pushing the performance.

• What’s happening with September? The last application processed was on September 7 and the month is still young.

New questions:

• Why is there a dip in May?

• Which product categories are doing well?

• Are we targeting the right customers or product values?

• How are our high-value clients doing?

The Outcomes

Without spilling any trade secrets, here is what happened:

• The leadership team was more engaged; excited by the new data points and empowered to take action.

• Project funding for the application was redirected. Instead of prioritizing new modules, a focus was made to improve the quality of life for the end users which helped reduce the data entry time significantly and improved the end results significantly.

• Respective teams were able to monitor the situation daily and were proactive with their actions. They could spot problems before they became problems and address them.

• Customers noticed the difference in processing speed, the word got out, and more people were attracted to these products.

• There was a direct impact on sales and performance.

• More questions were asked, leadership teams were more engaged and involved, and more analysis was done to solve more problems and drive fact-based decisions.

• Integrations with other reports and platforms allowed the end-users to get involved.

[insert link to interactive version]

What’s Next?

There is more that we can do to improve the report, but for now, this is a solid starting point to demonstrate this ‘new generation of reports’ and how data visualization tools can transform the way and the efficiency at which a business makes decisions. Look out for the next post on this topic, because I’ll go into more detail about how the dashboard was built and why I chose, and continue to choose these tools.

If you would like to try your hand at coming up with some more analysis let me know and I will happily provide access to the data!