ADP has built its Human Capital Management business on fast and accurate data. ADP’s comprehensive Human Capital Management (HCM) solutions require that HR, payroll and other data be integrated to deliver analytics and compliance services for 80 percent of FORTUNE 500 companies. HCM works with multiple other cloud-based systems to provide clients with the data they need. Therefore, its service experience is largely dependent on the right data integration methods and policies.
However, ADP faced a problem. Because, as was typical in the early 2000’s, they used a batch-oriented system with a very strict set of rules as to the format of the data, clients found the process incredibly cumbersome. If data wasn’t formatted correctly, it wasn’t accepted – leading to a lot of headaches and time lost. Working with Actian, ADP has made the move to a more open integration process. Today, it has succeeded in creating a user-friendly solution that has helped them grow their business by 20x while holding the line on costs. It has dramatically increased client satisfaction, and helped ADP become a major player in today’s HCM market.
The process was not always a smooth one though, and ADP’s Lloyd Turley, Director of CHSA Operations, sat down with Actian to discuss the challenges and his advice for those opening up their integration process. You can read the full Q&A here.
With 15 years’ experience under his belt, Turley helped ADP make the transition with the help of Actian. He provided some key best practices everyone should consider:
- Be a true data trading partner, which involves working with the people with whom you’re trying to trade data and really trying to find that middle ground. You have to break down obstacles and barriers and really reach out and collaborate to find common ground because typically there’s a customer in between that just wants things to work.
- Have some flexibility and the appropriate agility to collaborate. To achieve this, we have a data layer that we use to process both inbound and outbound data over which we have operational control – we don’t require many outside resources. This allows us to flex and meet the various needs in order to process data.”
- Be aware of error acceptance. People in our organization got accustomed to addressing and allowing an error because the error had always occurred. That needed to change when we started new integrations, as we were having to commit resources to address those errors. To fix this, we needed to address the behavior and process.
- Know what success looks like. Data integration can only work well if we really help establish the same goals across customers, partners and internal teams.
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