HOW TO SCALE
WITH VIVEK PATEL'S P.A.C.E. MODEL
THE P.A.C.E MODEL PLAYBOOK
When data analysts and scientists are hired within an organization for centralized analytic functions, they often don’t have the tools needed to scale analytics and drive business change—But that doesn't mean it's not possible.
Vivek Patel, the Head of Global IT Operations and Data Management at Ampere knows what it takes to scale enterprise analytics within large organizations. At Intel, he was able to help scale his team of 3 to a team of 35 in two years. And most recently, at Ampere he has helped scale his team at an impressive rate, keeping analytics a critical aspect of the organization.
Inspired by The Data Storytellers interview with Vivek Patel, we’ve outlined Patel’s 4 step P.A.C.E. Model to help you scale analytics in your organization:
GETTING TO THE ROOT OF THE ISSUE
We’ve all heard it repeatedly: Address the problem first. But what if your perspective is out of focus? Data analysts and scientists can make the mistake of focusing on big problems while overlooking day-to-day functional issues.
They go after creating impressive solutions with advanced tech, algorithms, or A.I. features. But often, the maximum impact lies in the small, seemingly boring problems that need to be addressed.
A game-changing solution could be something as simple as driving automation at a certain level or keeping better track of transactions within your enterprise resource planning systems.
GETTING TO THE
ROOT OF THE ISSUE
Approaching day-to-day functions might seem boring and without the glory or glamour of big tech solutions, but these seemingly mundane problems have the potential to impact the organization at a core level.
The key is getting to the root of the problem, which may be a simple fix that has an immense impact on company growth.
Rather than addressing an issue at surface level, get to the root of the problem with the 5 Whys Technique—A method created by Sakichi Toyoda.
If someone comes to you with a problem, keep asking why until you get to the root of the issue.
“The director isn't understanding my reports.”
“Your reports aren’t clear.”
“Because these numbers don't line up.”
“Because the transactions are coming in wrong in the system.”
“Because the data feeds are coming in through an SFTP upload as a CVS file and the vendor keeps changing things around.”
Solution: Finding the core issue.
“Because you haven't talked to the vendor and set up a standard process.”
In this case, you didn't need to reinvent a system, you just needed to correct the issue at a fundamental level. Fixed at this stage, analytics will be corrected and better integrated into your systems. While sometimes a new model can be valuable, often the solution is as simple as a correction.
USING DATA AS ACTIONABLE INSIGHT
All data, measuring systems, and KPIs aren’t of much value unless they are incorporated into an accountability system. Unless people are using data to hold themselves accountable, data governance will remain weak.
If you use analytics to track items such as over expenditures and allotments, you can use solutions to fix issues tracked by analytics to hold individuals and leaders of your organization accountable. As Patel says: “Embed your solutions in a manner where leaders and managers within the organization are utilizing it to hold their organizations and their peers accountable." This is how your analytics team becomes a critical function in your organization.
Schedule meetings with individuals in your organization to inform them of the patterns you are noticing. Then once they understand what the data reveals, teach them to use the data insights to hold themselves accountable for issues causing a bottleneck in your organization’s business growth.
Once people are aware of the problem created out of lack of accountability, individuals will start looking to analytics to maintain accountability.
To scale enterprise analytics, focus less on being the centralized function and more on getting people to use the data. Get to the root of the problem, hold stakeholders accountable by communicating in the best way for all parties involved, and empower them to create solutions that help them incorporate data into their operations.
Scaling is about taking gradual steps, pacing growth so that everyone is involved, and allowing others to create sustainable solutions that integrate analytics and drive lasting business change.
FINDING THE RIGHT CHANNELS
It feels exciting when you create a solution for a problem that will help close gaps and drive business growth, but how do you ensure people are using the solutions on a regular basis? How do you communicate with your stakeholders in a way that maintains accountability?
One of the biggest mistakes data analysts and scientists make when it comes to accountability is that they create the solution they think is best—Often in the form of a fancy dashboard or new model. But as Patel reminds us, most people in organizations aren't early adopters when it comes to new tech, so creating a new solution might not always be the answer.
To create the best solution, you have to take yourself out of the equation. This is where understanding your stakeholders comes in. Their preferred methods of communication may not be yours. You have to learn to meet them where they are, even when your method seems more efficient.
Learn your stakeholders' preferred modes of communication. As Patel suggests, if they prefer to receive information through a PowerPoint, send them a weekly PowerPoint in an email. You can even put a link to a dashboard accountability system you've created at the bottom of the message. This will help them familiarize themselves slowly with more efficient tools that can hold them accountable, without forcing a new system on them.
GIVE PEOPLE OWNERSHIP
One of the biggest keys to scaling enterprise analytics is giving people ownership of the solution. It's okay to give your stakeholders the data and allow them to come up with a solution that keeps them accountable. At the end of the day, the top priority is creating accurate data. We then need to ensure people are using the data, and integrating it into their operations.
Allow your stakeholders to be a part of the solution so they will feel empowered to use analytics in their processes. As Patel points out, it's not scalable for your analytics division to drive everything. Eventually, the data needs to be integrated within every division, and giving your stakeholders control to design their own solutions empowers them to integrate analytics into what they do.
The most important priority is that people are using the data. Empowering people to create data-driven solutions allows you to scale much faster than trying to control every aspect of how data is integrated within your organization.
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