Fix your data with dopamine

Our previous blog discussed the power of gamification and how firms can use it to improve data quality. This month I wanted to follow up on a related topic: the dopamine reward system behind fixing data problems.

Dopamine is the primary neurotransmitter responsible for motivation and reward. It can also enhance our depth of focus and lower our threshold for taking action toward specific objectives.

Doing something that feels good – such as setting and achieving goals, even small ones – stimulates the release of dopamine within the brain, creating a sense of accomplishment and pleasure in completing the task. Increases in dopamine levels enhance neural plasticity within the striatum and prefrontal cortex (the brain’s executive control portion), “resulting in improved cognitive functioning and overall well-being,” noted Bethany Medical Clinic practitioners.

As the eminent neuroscientist Dr Andrew Huberman explained, “when our dopamine levels are elevated, we tend to focus our attention on outward goals — the things we want — and we feel motivated to pursue them.”

We naturally seek more of these positive feelings by repeating the behaviour that made us feel good, locking attention onto the task. Neuroscientists refer to this as “intrinsic motivation” or self-directed learning.

It’s one of the reasons completing tasks on a checklist is so powerful. Checklists should be made up of small, short-term actions that feel achievable. Hitting those incremental goals then helps keep us motivated to continue to see through long-term projects and processes.

Small steps to better data quality

Big goals tend to be complicated and take time. They require sustained effort and patience. And they commonly fail. People suffer from overwhelm at the magnitude of the task. Focus drifts. Short-term priorities get in the way. They get frustrated, de-motivated and give up mid-project.

Data projects too often suffer this fate. Fixing data at wealth managers can feel like a huge, impossible enterprise. With good reason.

All wealth managers have data quality problems. That you’re not alone is heartening. But it can be unnerving as well.

When talking to prospects, we usually see one of two responses.

Some operations chiefs become terrified at how much the system will find. The scale of the challenge, and implications of all that bad data, are too daunting, preferring to take the approach of ignorance is bliss.

The alternative reaction is to embrace the challenge, accept it will take time and work and, like the saying about eating an elephant, start chipping away in priority order.

As the Bethany Medical Clinic observed: “Accomplishing smaller tasks is an invaluable stepping stone towards larger ambitions, thus creating a domino effect whereby each success further fortifies our desire for mastery over future challenges. This cyclical nature provides ample opportunity for continued growth while maintaining high levels of self-efficacy – ultimately culminating in enhanced personal satisfaction and neurological health.”

At DCI, what we’ve learned from this is to manage the process to avoid overwhelm. Experience has shown that the best approach is to drip feed in the system’s data rule checks. We turn on a few rules. It finds a quantity of items that are wrong. The operations team fixes those items. We then proceed to the next set of rules.

Breaking down the effort into bite-sized, doable chunks makes data remediation more manageable. And team members get the daily dopamine release from a task completed, with the motivation it breeds to check off more items and keep moving forward.

It’s a win-win. Wealth managers fix their data issues while promoting employee motivation and satisfaction.

Virtuous circle of data improvement

Importantly, it also creates a virtuous circle of improvement.

What we see with DCI system users is a powerful feedback loop. For example, we have a rule that checks a UK tax marker against end-clients’ addresses. After one wealth manager turned the marker on, the next day the DCI system flagged that they were missing the VAT on the management fees. The day after it pointed out they hadn’t set a CGT rate. Once the firm had set the CGT rate the system prompted them to set up the CGT allowance.

Team members quickly learn these chains, what is causing problems and the correct processes they should follow. So it acts as a great way to train staff and prevent recurring issues. Data quality inputs improve, staff can use their time much better and the company as a whole becomes more efficient.