Data maturity, Data structure, Data analytics… it’s all we hear and talk about lately.
Why is it so important and why has data become such a struggle?
Data is the new gold. We have to ensure we have insightful and powerful data to help our organization achieve their goals. But how does it all start. It almost feels like the right place to start is to look at our current data. Well, I am here to tell you, it starts even earlier than that.
Think about your data prior it ever being created. Think about actionable objectives, you can do now to help curate data gold. As I mention in my session at Gainsight Pulse 2022, there are 3 main strategies I live and breath by.
1. THINK WIN-WIN-WIN Solutions
This strategy is about ensuring everyone involved is winning. Think about your CSM needs, stakeholder needs and admin needs. Ask yourself key questions to help you understand how each player wins.
- Stakeholder: Can the business measure positive negative impacts to the customer through the data? Have you created autonomy around this data?
- CSM: What efficiency have we brought to our end-user from the pervious processes? Are we creating a one-stop show for our end users?
- Admins: Can we easily build on top of this? Howe much maintenance or tech debt is this going to create.
2. BEGIN WITH THE END IN MIND
Remember GPS needs an address to find a route and so do you. Get the details of what we are trying to accomplish with the below questions.
- Understand the Ask: What actions are we driving for our CSMs? What do we want to accomplish with our customers? How are we going to measure success?
- Explore every option: What features would you use to solve this? What data structure is necessary to measure out efforts?
3. FUTURE PROOF YOUR BUILD
Do what’s right not easy. Make sure we are thinking about the future of your data.
Where do you see your build in 6 months to 5 years? What do you want to measure in the future?
- Do your Data research. Get a data sample and examine it for every new data set.
- Identify the key data points needed and exceptions to the data needs. We all have dirty data, lets own it and accommodate.
- Review what you have found with your collaborating partners. What are the specific requirements you know we need to solve our solution and for future solutions?
Every industry is customer obsessed and as admins remember our Stakeholders and End-users are our customers. Treat them as such.
For all the stakeholders and CSM out there, remember there are so many technical challenges that admins face every day.
Collaboration and patience will help you find your balance for the WIN-WIN-WIN strategies.
Q&A
I wanted to include a few questions that I absolutely loved and wanted to give a deeper response to.
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What books and/or educational material do I read to help me grow?
The books below have helped me adopt transferable skill sets that I use to help my data strategy and tough conversation with my collaborating partners.
- The 7 habits of highly effective people by Stephen Covey
- Crucial Conversation
- The speed of trust by Stephen Covey
- Learn from each other. I have learned so much from my data team, SF Team, and business.
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What function or role should be the one who stewards the enterprise data strategy across the company?
It depends on your organization and what level of maturity they are at. Companies with highly mature data strategy models have an org channel that handles it. For those companies get to know your companies’ data strategy and adopt it for your application. No need to re-invent the wheel and by being on the same wavelength as your organization the data become easier. Other organization that are still ramping up to attain advance data maturity might not have a solid plan for your application. Let’s curate our data to be flexible and agile. Start asking other application owner their strategy and collaborate on simple things such as sharing protocols and how to start a MDM (master data management).
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How do you address the difficult conversation with a stakeholder that their ask doesn’t meet the win-win-win approach?
Stakeholders respond better to visuals and a great story. Help them see how you use data analytics to drive better decision and how they can do the same. I use the Proof-of-Concept theory to help demo out possible build options and measuring options. To all the players (stakeholders, CSMs, and admins) be patience this will come with trust. Also, I think this would be a great session for next year. 
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Any guidelines on when dashboard should be created and live in Gainsight versus a separate BI tool (EG Tableau)?
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@gsombatsaphay (Gina Sombatsaphay)
This is a fun challenge for me. For me it’s about how often do you want to see this data. Are we measuring this WoW, MoM, or YoY? How many people want to see data and what segmentation do they want to see? If CSM/Manager both want to see the same report but from their level a dashboard, make sense. If the whole organization needs to see this data, then BI tool makes sense. I would add a 3rd question here, how granular do you want this data analytics? Granularity make sense within the tool, as the tool has features to help connect all of the segmentation. Adoption explore (Gainsight Feature) data I tend to challenge exporting out of the tool. Those analytics only work in Gainsight.
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What model or method would you recommend for feature selection with customer data?
This goes back to the right tool for the right job. Create a standard way of evaluation this ask. There is always more than one solution and standardization will help you and the organization simplify how you do things. A notable example is figuring out when do you create look-up values versus using data designer? Look-up values are for those object that have long-term correlation. Data Designer is used for short term connections such as incident resolution. Once I decided this governance for our application, I shared it and now everyone is on the same page of how to use these features. So create that standardization for your organization.
