Data to see the future

Written by Carrie Majewski, Advanced Analytics, SQA Group

For many companies, data wins start simple… albeit powerfully. Businesses invest in standing up baseline data foundations (e.g. data collection and storage, quality, literacy training, tools adoption etc.) so that they can start knocking out wins such as….

Establishing trackable KPIs/OKRs at departmental levels

Using dashboards and visualizations to convey data more powerfully

Increasing data literacy org-wide

Leveraging data to set direction and see what is and isn’t working

Creating a culture of accountability via monthly/weekly report outs

Huge and important wins!

But as companies advance along their maturity journey, how they want to win with data often starts to change. They begin eying things like AI/ML adoption and acceleration, progressive KPI-ing (more on that here), eliminated data siloes, data science, automated analysis delivery and… for many…


Predictive analytics. Or using data to shift from asking “what happened?” to “what might happen?”

At the simplest of levels, predictive analytics is about leveraging advanced analytics and modeling techniques to make predictions about the future… future outcomes, trends, customer behavior, macro events, organization performance, etc.

Companies can leverage predictive analytics across so many different domains and focus areas from answering questions about buying behavior to supply chain management to product development to risk management and so on. In fact, it’s become such a pervasive focus and investment of leaders across all domains that the predictive analytics market alone is expected to grow from $12 million in 2022 to $38 million by 2028.

So, what steps can you take today regardless of the functional area you support? Here are a few quick tips:

  • Data as Treasure: What role do you want data to play in your day-to-day? Do you want it to be a core team member whose main focus is to “report the news,” or share what happened? Or do you want it to be a treasure? Trustworthy, full of insight, and rife with untapped opportunity worthy of steering your future. The role you want data to play is in fact a choice. Because no mater the functional area you lead, once you decide the significance of data in shaping both your day-to-day and future objectives, you can turn attention to making sure data foundations are in place — storage, quality, governance, literacy, etc. — so that you can then leverage advanced analytics and AI/ML techniques to turn your trusted data into a treasure of possibility. Lean into your partnership with your data/tech peers (or a third-party provider) to ensure you are fortifying the core pillars of your data ecosystem so that you can pave the wayfor data to be a business treasure.
  • Think Like a Futurist: According to research from the Institute for the Future, as a human population, most of us naturally struggle to think about the “far future.” In fact, 27% of Americans rarely or never think about their lives five years from now, as compared to 60% who think about the near future — one month from the present — every day. As you reflect on your relationship with the future, consider how this might help or hinder how often you spend time pulling your team, department, or organization to the future. For example, do you spend more time reviewing historical or current data? Predicting no more than a few weeks out? Forecasting months and years out? As you shift towards prioritizing predictive analytics, see if you can also strengthen your personal focus on the future, channeling the mindset and behaviors of Futurists.
  • Identify and Aim: Instead of starting big — going from descriptive to predictive team or organization-wide — consider picking a specific use case against which having predictive analytics would greatly help. For example, do you most need insight into customer buying patterns? Pricing models? Risk mitigation? Cash flow? Product stickiness? Once you have your top use case identified, work with your data/tech teams on building specific models and analyses with the data you already have (or pinpoint the data you need to begin tracking) and start deriving insights for that specific opportunity at hand. Leverage this mini use case to establish the proof of concept and generate the momentum needed to then drive greater predictive analytics impact.

Your journey from descriptive to predictive can begin at any time. And it often just starts by asking one simple but powerful question… what might happen in the future with our business?

Originally posted here

Read More AI & Data

Comments are closed.