data science

The Data Science Race Companies Are Losing and 3 Ways Startups Can Run Right Past Them

Most organizations are sitting on the sidelines when it comes to taking advantage of data science, and that gives you the opportunity to disrupt them.

In the race for the next big deal, companies need to make good business decisions to win. More than ever before, those decisions need to be data-driven business decisions.

Surprisingly, Forrester research shows that companies analyze just 12 percent of their data, which means 88 percent of it goes to waste.

That’s like prepping for a race by only working out your legs, which as we all know is a sure way to end up out of breath!

Here’s your biggest hurdle: to beat leading companies that already have a head start, your organization needs to be able to make data-driven decisions across your whole team, from your social media expert to your HR lead.

But here’s reason for hope: building a data savvy team doesn’t mean that all your employees need to be data scientists. Let’s look at the three exercises you should be doing to help you pass the finish line ahead of your competitors.


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Exercise #1: Train your non-technical people in the basics of data science

To give your team a leg up, every employee should be upskilled to the point where they have a sufficient level of data competency to make decisions in your startup’s best interests. Is your marketing person (just to take one example) skilled enough with data to take advantage of opportunities hiding within it?

Let’s say your customer success team is looking through your CRM system, and the data shows that most of your leads are coming in through your website. Will they be able to recognize this in the data? If so, are they data savvy enough to decide that optimizing the site’s SEO is more important than spending time at conferences?

Across all non-technical functions at your startup, your team needs to be able to make these kinds of decisions. After all, your whole body needs to work in unison to put you past the finish line.


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Exercise #2: Keep your technical employees on the cutting edge

Any athlete should be in peak condition, and the same goes for your technical employees’ skills. Do your tech people have the opportunity to attend conferences and workshops to keep their skills honed? If you can’t spare their time or the travel costs, can you connect them to online versions of those events? Do they know how to build the database infrastructure needed to accommodate the huge amounts of data used for cutting-edge work?

One of the most powerful things about data science, as well as its ability to help you disrupt your field, is that there’s always new breakthroughs to take advantage of. Constant training is key to upskilling and retaining tech talent who can lead data science efforts at your startup.


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Exercise #3: Help your non-technical and technical people communicate with each other

This exercise is more rigorous than it sounds, as most tech people haven’t developed the muscles of identifying business problems, translating them into data problems, and then translating solutions back to the business side.

Meanwhile, non-technical people often don’t know how to work with data to answer basic questions like, “Why are my customers leaving?” In short, your tech-savvy team needs to be trained on how to answer business questions, and your non-technical talent needs to be trained on how to leverage data.

Ideally, both sides should be able to:

  • Ask each other the right questions
  • Assess data sets
  • Identify the most important deliverables
  • Manage expectations
  • Discuss technical processes with one another

Without data and business savvy on both sides, you’ll be required to coach a team that speaks two different languages, frustrating your efforts to catch up to and surpass your competitors.

Working on the three exercises above are crucial for any organization, and those who don’t are setting themselves up to stumble. Now that you understand the race and how you can train for it, what will you do to drive data-driven decision-making at your startup? It’s time to get into the game.

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