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Data and the future of work

Busy,Working,Day.,Side,View,Of,Successful,Trader,Or,Businessman

Written by Carrie Majewski, Vice President of Growth Strategy, SQA Group

When was the last time you looked at your approach to KPIs through the lens of… what if what we are measuring needs to change? Hear me out… 

As leaders, we tend to get really comfortable with what we’ve always measured.  

Pipeline
YoY Growth
MQL to SQL conversion
Website traffic
E
mployee retention
C
ost per customer acquisition
Net Promoter Score
E
mployee Pulse Scores
… and so on and so forth 

In fact, many times, we bring these KPIs with us from company to company. We join a new firm, hone our strategy, examine existing departmental performance, and rally our teams around the weekly and monthly KPIs we will examine to track efficacy against goals. Different company. Different team. But all too often, the exact same KPIs we’ve always tracked. 

But here’s the thing… 

We know the business world is in a revolution. Companies are evolving their models at a rapid clip. The pace of innovation is accelerating at lightning speed. Teams are working, collaborating, and partnering today in a way they never have before. New business concepts like hybrid work, asynchronous schedules, distributed workforces, to name a few, have become critical parts of our new vernacular. 

And if our businesses, people, and worlds have fundamentally shifted, then what we measure needs to change.  

If we remain tethered to tried-and-true KPIs — like those listed above — we are only measuring a small fraction of our current reality. 

So how can we re-examine how we are leveraging data and advanced analytics solutions to fuel our next era of growth? Here are 3 places to begin: 

 

Elevate that which scares you

Data can show us the parts of our business that are in need of our greatest attention. Customer churn increases tell us to look at things like customer service, product impact, pricing, competitor landscape, etc. Employee quits force our attention towards things like culture, leadership, and benefits. Slow product release cycles require us to look at our SDLC, team methodologies, and organizational bottlenecks. 

But what if we elevated the things we are most afraid of before they happen? Using data to measure things like: 

  • How inclusive is our culture?
  • Do we innovate as fast as our competitors?
  • Do we act in alignment to our mission and vision?
  • How psychologically safe does our team feel?
  • Are we truly differentiated, or quickly falling mainstream?
  • Are we among the Early Adopters for innovation, or slipping into the company of the Late Laggards?

In other words, consider using data and analytics to predict what could happen before it ever does. Reporting on employee attrition percentages AND psychological safety scores. Monthly renewals AND product market resonance. Growing sales pipeline AND client vitality scores.  

If we start to measure the questions we most need answers to NOW, we can get ahead of the consequence that happens when we don’t take action address today. (Our CEO Rob Lanza recently wrote on the concept of being able to measure anything; check it out!).  

 

Tap into your dark data

Without getting too techie here (I’ll save that for our amazing Advanced Analytics team!), it’s time to talk about dark data.  

Dark data is information your company collects, stores, and amasses through normal business activities (emails, customer call records, raw survey data, social media numbers, financial data, etc.), but is not tapped for purposes like analysis to steer business decisions, initiatives, and pursuits. And the more dark data remains unused and dormant, the more likely you are missing opportunities to tap into one of your greatest organizational resources.  

The IDC estimates that only 1% of the world’s data is analyzed. That is a lot of unused data! 

In the modern work era, we are turning over stones that have never been turned before — in an exciting way! We are asking new questions like, “Should we opt for self-organizing teams over hierarchies?”, “Are we automating what should no longer be manual?,” “Are we using technology for good?,” “Are we socially responsible as a business?,” and so on and so forth.  

Another stone to turn over? 

Are we sitting on a wealth of insight via our data that could help us not only turn over stones, but know that as we do and take action, we are doing so because of what the data is telling us, not just what our guts suggests? 

 

Dabble in “Advanced”

There are so many exciting things you can do with data, from building machine learning models to implementing AI solutions to leveraging sentiment analysis and so on.  

As you look to elevate the role data plays within your organization, embrace the “advanced” part of advanced analytics. These solutions are not mystical, far away, or only for the large enterprises. They are here today.  

Just consider a few statistics… 

The number of companies using AI in business grew by 270% between 2015 and 2019 

72% of companies using AI believe it will make their jobs easier 

65% of companies planning to adopt machine learning say the technology helps businesses in decision-making 

91.5% of leading businesses have ongoing investments in AI 

As you begin to think of the role advanced analytics solutions can play in your organization, consider that: 

  • Emerging is always in the eye of the beholder. No matter where you are on your data journey, it’s OK! Just resolve to take one more step forward today. 
  • The barrier to entry for adopting AI, ML, NLG, etc., has never been lower. We are not talking about years. It can happen in weeks. 
  • The tech side of the business is not the only side driving advanced analytics adoption. The business side — think marketers, sales, HR, product, etc. — are owning a massive part of the advanced analytics budget.  In what ways do you want to drive adoption forward in honor of your department, team, and personal leadership? 

We are re-examining so many critical parts of our business these days from service offerings to team structure to go-to-market initiatives to market penetration, among countless other areas. As you do, consider… 

Are we also re-examining our approach to how we use data? Or is our data still living in a different workplace paradigm? 


Originally posted here

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