The Problem
A leading real estate company increased the end-to-end visibility of its customer service operations and internal workflows. Due to the rapid growth and acquisitions, the company ended up with a complex IT landscape with dozens of legacy CRMs. The main goal was to increase the visibility of workflows in order to improve automation levels, make better business decisions, and ensure accurate billing of out-of-scope requests. The client is a leading real estate management company experiencing rapid growth through acquisitions. The organization previously tried traditional process mining to shed light on its business challenges and to understand process flows better. However, this attempt failed because of a mixed IT landscape with legacy CRMs brought over by acquired companies. This resulted in highly variant workflows over dozens of IT systems, portals, and documents.
The Solution
The customer service unit responded to 7,500 requests monthly, 10% of which had already been automated. Unfortunately, the customer couldn’t map any more workflows beyond that manually, and thus the visibility across processes was highly limited. The event log extraction-based method used previously was unsuccessful because it overlooked the majority of the workflows happening across different systems. Moreover, it failed to bring business insights into the time usage per customer. The client wanted to understand how the process flows overall, as well as where the time is spent in each of the process steps. Every customer request was to be mapped to each workflow to identify and prioritize the most impactful automation targets. The issue was further complicated by the following characteristics of the process:
- Work happens over 10+ different legacy IT systems and supporting applications.
- Customer requests are of such diverse nature and require such different actions across business applications that it’s impossible to identify repetitive actions manually.
- Management fears that employees aren’t billing out-of-the-scope requests that should be billed separately.
With ProcessMaker Process Intelligence, they analyzed all customer service operations in one country, covering 3 teams and 65 customer service agents. The focus was to:
- Identify the time used per customer and separately billable work to bring better business decisions and verify the accuracy of invoicing.
- Find repetitive and automatable workflows in prioritized order for quicker customer request resolution to improve customer experience.
The Value Created
Within 4 weeks of using ProcessMaker’s Process Intelligence software, the client was able to successfully identify the gaps in invoicing that caused them 5-figure losses in the tracking period. The customer also identified 5+ customer requesttriggered workflows that they can automate with a robotic process automation (RPA) solution to cut manual efforts, increasing the automation ratio by 10% and decreasing time to resolution from days to minutes. In addition to the project scope findings, the customer learned that:
- The share of the customer request-related work was below 50%, compared to the expected 85%, meaning that the share of “other” nonimportant work was higher than the planned capacity level.
- 10% of customer requests were opened/touched, but not taken action upon. These were probably seen as problematic/hard cases to be solved, causing delays in customer responses.
- 30% of employees were still using their old work practices, which were replaced already 4 months ago, instead of the new prioritize → solve → report approach
