2022 gave way to a virtual and complex business landscape. Complex metrics started to shape our world. Given the major shift in the paradigm, the destiny of businesses is indirectly being placed in the hands of data analysts or scientists who are relied upon for delivering insights for growth acceleration.
With all these implications, one might think that organizations are now entirely dependent on D&A’s insights for their growth and prosperity. Unfortunately, according to KPMG’s new report (Building Trust in Analytics: Breaking the cycle of mistrust in D&A), only 38 percent have a high level of confidence in the insights. Analysts need to build trust to generate value from the data to fuel growth.
The role of trust in an analyst ⇔ stakeholder relationship
Trust is an accelerator in the context of analytics. When an analyst builds trust with his/her stakeholder, the stakeholder is more open to the analysts’s insights and recommendation. The greater the trust, more quickly the stakeholder is ready to act on the insights and faster would be the results. Thus trust accelerates impact from data.
Trust and credibility go hand-in-hand. Trust is essential for an analyst/data scientist whether they work internally with a stakeholder or externally with a client because it will accelerate the impact they have can drive.
How do you build trust?
Building trust is a process. trust results from consistent and predictable interaction over time – Barbara M White
Whether you are hired as an analyst or a product manager or as a VP, you need to build trust that mirrors your integrity. Here are some thoughts on building trust that has helped me and my team.
There are four anchors to building trust.
We do what we promise to do. If we promise our clients to deliver a document by such and such a date, we make sure we get them that. That’s the first level of trust. It may be in timelines or the activities we will do, etc.
We show respect, and we build respect –
As we all know, respect is a two-way street. Where we give respect, we get respect. For example, we dress up right for the meeting. We show up on time. We particularly show people that we respect them. It’s just not the lip service. We respect their time, their insights, hear them out when they have a perspective. We do not put them aside, saying we know better because we are the experts. We believe in collaborating to build a bigger picture that helps all of us. Giving respect gets you to respect that’s the law of nature and law of behavior.
Making things easy –
We make things easy for our clients and our collaborators. Whether we are joining in an advisory role or data scientist role or an analyst role, we make things easy for the other side. How do we do that? We provide timelines and we stick to them. We say “Hey give us inputs by this time”. We ask clarifying questions about their expected timelines. In doing that, one can choose ease for oneself and will start building trust too.
We get stuff done –
“The proof is in the pudding”
Whatever you may say, at the end of the day, the proof is in the pudding. Meaning it’s not about the amount of effort you make, it’s about the results you drove.
This doesn’t essentially mean working hard. It means working smart or adopting the best strategic approach. This saves a lot of time for our clients and collaborators. For example, if a treasure has to be searched in the Pacific Ocean, we do not boil the entire ocean for the treasure. Instead, we identify four or five high probability spots where we can find the treasure and search in those places. Precisely, we work strategically to accomplish our goals within the shortest period possible.
These are the core to how we function, how I function, and how I invite those who are around me to build that trust.
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