Why enterprises should put data analytics in the hands of every employee

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After more than a decade of consistent growth, we have entered a phase of radical change, which creates both risk and opportunity for enterprises. We no longer can count on linear revenue growth based on an expanding economy fueled by cheap capital; we must now rediscover our ability to drive efficiencies while also finding the disruptive opportunities that unpredictable environments tend to create. Great companies emerge from these eras while average ones fail. The stakes are high.

The best enterprises are recognizing that:

  • Demand is hard to measure and constantly changing given the macroeconomic environment.
  • Supply chains are even less predictable given today’s constant changes, and both labor and logistics constrain decisions.
  • Growth matters, but we now have a greater emphasis on the fundamentals (that is, profit) than we have had in over 15 years. Profit is the new growth.
  • And investments in tech are still holding up (even with cuts). Boards are acknowledging that the future is in navigating the items above with more accurate and more compressive data, faster decision-making, and tighter cybersecurity as top spending priorities. 

Intense competition means every action must, with a sense of urgency, lead to a winning result — an outcome that bolsters revenue and profit while reducing risk. Data is playing a more critical role than ever. It provides insights into customer behaviors, just-in-time inventory and capacity management, and a look into the corners of each department (billing collections, procurement and beyond) for savings that can make the difference. Most importantly, data is the fuel behind innovation, helping companies sift through disparate sources for insights into opportunities. 

The real value of data analytics

Data analytics is employed to make daily strategic and tactical decisions faster and better. For example, live inventory data integrated with real-time, granular sales data provides the enterprise a much clearer understanding of how to spend cash. Going further, the ability to plan OPEX in real-time (rather than quarterly) with live headcount, sales numbers and disparate other data creates a much better picture enabling not just C-level executives, but everyone who can now access the data, to manage the business. Before the advent of cloud data warehousing, these were all in different systems, and consequently, decision-making was less informed and more reactionary. That was not only bad for business but bad for culture; how many of us remember the “no more hiring this quarter” type of blunt budget management that would come down from on high without notice? 


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Finding value in data isn’t only about analyzing it (which is a whole other benefit). It’s an entire discovery process that requires insightful analysts, curious business users and executives who ask targeted, strategic questions. 

We must start by enabling people at all levels of the organization to input the right data. (As they say, “garbage in, garbage out.”) We know a company that has staked 25% of its company bonus on the quality of data — and has subsequently moved from “reporting” (batch data) to event-driven (don’t look at data because it’s Friday, look at data because it changed meaningfully and new decisions must be made). Last, it is about finding/enhancing new data sources (enrichment) and building new models for the future, so you are more prepared.

What’s ironic is that while it will probably be someone in the C-suite who signs off on the next breakthrough data analytics enterprise product, that product will, for the first time, be in the hands of many professionals across the enterprise — not just those of a data scientist and several top executives. And better yet, the data itself will be in the hands of the people who take action on a daily basis rather than a cadre of executives who have access only to summarized reporting typically presented in visualization tools.

Many in the business world like to be able to say that their best business decisions are “data-driven.” Too many use data analytics to substantiate or prove their pre-conceived strategic endeavors or business models. This, to me, is a half-baked application of data analytics, falling short of full-throttle investigation and identification of data to reveal real trends and enable the best possible business decisions. 

To access the full value of data analytics, fantastic volumes of data must be accessible with velocity, in real time, across many corporate departments — sales, product development, supply chain logistics, CRM, marketing — to foster collaboration while discovering trends and unearthing new arenas for profit and best practices for optimal outcomes.

A wide spectrum of business professionals harnessing big data and analytics in real time

The rise of no-code/low-code applications and software is a game-changer for non-technical business users. Every company, regardless of industry, is becoming a data-driven business, and no-code data and analytics can now be in the hands of a wide spectrum of business professionals. 

No-code/low-code is changing the future of work for marketers, analysts, product managers and other key decision-makers outside the data science team. 

Game-changing technology requires democratization

Letter writing and mail delivery gave way to the telegraph accessible at the railroad station, which would later be replaced by the telephone, which would eventually be supplanted by smart, personal mobile phones with their plethora of communications functions including email access and text messaging.

Similarly, computing started with large machines located in a room in a corporation, which would evolve into personal computers, and then laptops, which would later give rise to computers on small mobile personal devices.  

The accessibility of these latter technologies fortified by applications that promote collaboration drove exponential growth in their use. The “everybody’s using it” dynamic has a fulfilling consequence of stickiness and consistent new sales growth coupled with repeat sales.                

We are on the same path with data. The fundamentals changed over the past 15 years (cloud computing, declining storage costs, diverse new data sets and rapid data growth, cloud databases, data marketplaces). What is left is creating the “consumer” experience for what has been a highly technical feature set in analytics. 

Avoiding bottlenecks with data analytics

Access to data analytics by a wide variety of enterprise professionals can happen if new tools and solutions promoting the democratization of “big data” get off to a smart start by following these guidelines:

Enter the market via the current technology stack

If you’re going to bring forth a new technology/product/solution/tool that will create significant advantage, it is helpful to have it compatible with an existing platform successfully used by many users. Creating a tech stack aims to maximize efficiency, productivity, performance and security throughout the website or app development process. With the right tools and technology at their disposal, developers can build a product much faster, with fewer roadblocks, and predict how much time and budget the project might need.  

The tech stack developers use will have an impact on how your product will function now and in the future; how easy to maintain and scalable your product will be; how well your entry will perform; how and where the data inside it will be stored (local or cloud); and more.

Ensure your product performs well (and can be reasonably maintained) in the field

The example of the runs-when-it’s-flat tire comes to mind. Wrote one individual driving a BMW with such a tire, “There’s a lot to be said for the reassurance of driving on a flat after you’ve had a puncture, but if you want my advice, skip the run-flats. One-time, conditional convenience is nice, but in the big picture, run-flats are likely more trouble than they’re worth.”

Make sure your product can function with current infrastructure. Tesla founder and CEO (and now Twitter owner) Elon Musk launched his innovative car company with the mission “to accelerate the advent of sustainable transport by bringing compelling mass-market electric cars to market as soon as possible.” This mission is the backbone of Tesla’s successful business model. There is nothing needed from Tesla to change the roads.

Identify and avoid naysayers

Do your homework about the industries and companies you believe you can best convince that your entry’s benefits are readily visible and embraceable. Have they adapted quickly to changes in IT infrastructure, or been slow to respond? Have they been among the first to invest in emerging technologies or, like sheep, did they wait and follow the herd? There’s a hilarious television ad that captures the frustration of dealing with naysayers, featuring celebrity-curmudgeon Larry David, creator of “Seinfeld” and “Curb Your Enthusiasm.” He’s cranky. And so he was cast in a clever ad campaign as the “I hate it guy” throughout history — when the wheel was brought forth; the fork; the toilet; coffee; democracy; the light bulb; traveling to the moon; electric vehicles. The campaign, created by crypto company FTX, is punctuated by the tagline, “Don’t be like Larry.”

Yes, we have a fair share of naysayers in technology and in other industries where new approaches are introduced to win the day. Naysayers are resistant to seeing the world in a different way — they are those who fail to see the possibilities that a new solution offers. They threaten business progress and may even accelerate an organization’s decline.

Mike Palmer is CEO of Sigma Computing.

Originally appeared on: TheSpuzz