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Put the Power of Data Analytics to Work for Your Business in 2019

Today, the thought of tapping into the vast and expanding reservoir of data that resides inside and outside a business can seem overwhelming. Yet, it’s increasingly difficult for businesses to remain viable without making the effort.
Consider: Just a decade ago, the sum of all data (public and private) equaled around 1,000 Exabytes (i.e., billions of gigabytes). That may seem like a lot; but today, it’s around 30,000-plus Exabytes, or put another way, 30,000-plus quintillion data points (translation: lots). By 2020, that already gargantuan volume of data will double in size, with more exponential growth slated for the years to come.

No matter what business you’re in, data matters – today more than ever – and there is a strong business case for properly leveraging it. Conversely, ignoring it – or deemphasizing its relevance – will probably cost your business in ways you may or may not immediately recognize.

If you own or operate a business, ask yourself:

  • How can I understand what my customers are thinking, and what’s driving their buying behavior?
  • How can my sales and marketing team increase sales?
  • Is my team being efficient, and how do I know?
  • What are today’s buying trends?
  • How can I stay closer to my customers…increase their loyalty…win back customers that I’ve lost…and understand why they left in the first place?

Finding answers starts by asking four primary questions:

  • What happened? (in business consulting circles, we call this Descriptive Analytics)
  • Why did it happen? (aka, Diagnostic Analytics)
  • What will happen? (aka, Predictive Analytics)
  • How can we make it happen—or prevent it from happening? (aka, Prescriptive Analytics)

Data analytics plays a key role in addressing each question. You start by applying descriptive analytics to question #1. For example, if you feel you have fewer customers today than you did at this same time last year, descriptive analytics bring the issue into clear focus. Essentially, they describe what happened.

Next, diagnostic analytics converts data into information that can be used to understand the reasons behind an issue. In the example above, that 20 percent decrease may be traceable to a better-engineered and less-expensive product offered by a new competitor.

From there, predictive analytics is used to answer question #3 (what will happen as a result of this better, faster, cheaper product); and prescriptive analytics provides insight to help you respond appropriately to this threat. As this process unfolds, hindsight leads to foresight, which enables your business to spot and anticipate trends both internal and external, and plan accordingly. You can attempt this based on experience or intuition, but numbers don’t lie.
Data analytics applies to businesses of all sizes and scopes. In this digital age, businesses aren’t being disrupted by the competitor down the street. Rather, established businesses and startups halfway around the globe are turning bold ideas into disruptive technologies, products and services that affect your business. If you aren’t leveraging the vast pool of available data to become smarter at what you do, rest assured they are.

Understanding the Value of Different Types of Data

Data engineers and scientists call some of today’s expanding data pool structured data, and it encompasses things like CRM and ERP stats, census data and more. Certainly, this is useful information. Yet, an exceedingly large proportion of this data is “unstructured”—i.e., survey results, social media posts and video content. If you’re looking to get inside the hearts and minds of customers and prospects, this is where to look.

Unstructured data reveals what your customers and prospects are saying about your business in an environment you don’t control. While their criticisms may be hard to swallow, their insights are honest, and valuable to your business.

Getting Started – 5 Steps to Success

When I speak about data analytics to clients and business leaders, the question I most often hear is, “How do I get started?” I believe this path unfolds in 5 distinct stages:

  1. Start by asking the right questions. What’s happening that affects the business, from small issues to large ones.
  2. Acquire data – internal, external, structured and unstructured – then convert it into information to create value.
  3. Focus on high-impact areas. Data analytics products can be tactical when necessary, but you’ll want to focus your time and resources on endeavors that create the best possible business outcomes for your enterprise.
  4. Use the right tools. It may be wise at this stage to reach out to data analysts, data engineers or even data scientists for help in leveraging data to impact your business. Based on the business objectives you’ve established, it could be money well spent. Additionally, trusted business consultant can ask and address the right questions, and ultimately, help navigate you toward the right solutions.)
  5. Tell stories. Stories connect with people; the meaning and impact really resonate more strongly than raw facts and figures. Specifically, they illuminate and turn raw data into understandable insights. The number seven is pretty meaningless by itself without putting it in some context – for example, disclosing that last year, Business XYZ grew by three percent while its competitors grew by five percent—and XYZ’s goal was to grow by seven percent more than last year.

Bringing sense and understanding to raw data, facts and figures is critical. Historically, business leaders and owners have relied on intuition and experience to address rapidly changing opportunities and challenges. With a global economy and fast-moving competitors, it may not be sufficient to solely rely on intuition and experience any longer. Capitalizing on the data that surrounds us and can inform us is too big an advantage to ignore any longer.

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