Why companies should put data analysis in the hands of all employees

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

The best companies are recognizing that:

  • Demand is difficult to measure and is constantly changing given the macroeconomic environment.
  • Supply chains are even less predictable given today’s constant changes, with both labor and logistics constraining decisions.
  • Growth matters, but we now have a greater emphasis on fundamentals (ie earnings) than in the last 15 years. The gain is the new growth.
  • And technology investments are still holding up (even with cuts). Boards are recognizing that the future lies in navigating past items with more accurate and comprehensive data, faster decision-making, and tighter cybersecurity as top spending priorities.

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

The real value of data analysis

Data analysis is used to make daily strategic and tactical decisions faster and better. For example, live inventory data integrated with granular, real-time sales data gives a business a much clearer understanding of how to spend cash. Going further, the ability to plan OPEX in real time (rather than quarterly) with live counts, sales numbers, and other disparate data creates a much better picture that enables not just C-level executives, but all They can now access the data. manage the business. Before the advent of cloud data storage, everyone was on different systems, and as a result, decision making was less informed and more reactionary. That was not only bad for business but also bad for culture; How many of us remember the hard-hitting “no more hiring this quarter” kind of budget management that would come from the top without warning?


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Finding value in data isn’t just about analyzing it (which is another benefit). It’s quite a discovery process that requires insightful analysts, curious business users, and executives asking specific strategic questions.

We must start by enabling people at all levels of the organization to enter the correct data. (As they say, “garbage in, garbage out”). We know of a company that has bet 25% of its enterprise bonus on data quality, and subsequently moved from “reporting” (batch data) to event-based (don’t look at the data because it’s Friday, look the data because they changed significantly and new decisions must be made). Ultimately, it’s about finding/improving new data sources (enrichment) and building new models for the future, so you’re more prepared.

The irony is that while it will probably be someone in the C-suite who approves the next innovative enterprise data analytics product, that product will, for the first time, be in the hands of many professionals across the company, not just those of one scientist. of data and several senior executives. And even better, 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 only have access to summary reports that are 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 analysis to substantiate or test their preconceived strategic projects or business models. This, to me, is a half-baked application of data analysis, falling short of full-speed data research and identification to reveal real trends and enable the best. potential business decisions.

To access the full value of data analytics, large volumes of data must be accessed with speed, in real time, across many corporate departments (sales, product development, supply chain logistics, CRM, marketing) to drive innovation. collaboration while discovering trends and discovering new ones. arenas for profit and best practices for optimal results.

A broad spectrum of business professionals leveraging big data and real-time analytics

The rise of no-code/low-code software and applications 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 broad 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 of the data science team.

Innovative technology requires democratization

Letter writing and mail delivery gave way to the telegraph accessible at the railway station, later to be replaced by the telephone, which would eventually be replaced by smart personal mobile phones with their plethora of communication features, including access to mail email and text messages.

Similarly, computing began with large machines sitting in a room in a corporation, which would become personal computers and then laptops, which would later give rise to computers on small personal mobile devices.

The accessibility of these latest technologies strengthened by applications that promote collaboration fueled an exponential growth in their use. The “everyone is using it” dynamic has a satisfying consequence of stickiness and steady growth of new sales along with repeat sales.

We are on the same path with the data. The fundamentals have changed in the last 15 years (cloud computing, declining storage costs, various new data sets and rapid data growth, cloud databases, data marts). What remains is creating the “consumer” experience for what has been a highly technical feature set in review.

Avoid bottlenecks with data analysis

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

Enter the market through the current technology stack

If you are going to introduce a new technology/product/solution/tool ​​that will create a significant advantage, it is helpful if it is compatible with an existing platform used successfully by many users. Building a technology stack aims to maximize efficiency, productivity, performance, and security throughout the website or application development process. With the right tools and technology at their disposal, developers can build a product much faster, with fewer hurdles, and predict how much time and budget the project might take.

The technology stack that developers use will have an impact on how your product will work now and in the future; how maintainable and scalable your product will be; how well your input will work; how and where the data it contains will be stored (local or in the cloud); and more.

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

The example of the tire that works when it is punctured comes to mind. Wrote one person who drove a BMW with such a tire: “There’s a lot to be said for the comfort of driving on a flat surface after you’ve had a flat, but if you want my advice, skip the flats. The 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 work with the current infrastructure. Tesla founder and CEO (and now owner of Twitter), Elon Musk, launched his groundbreaking car company with a mission to “accelerate the advent of sustainable transportation by bringing compelling mass-market electric cars to market as soon as possible.” This mission is the backbone of Tesla’s successful business model. It doesn’t take anything from Tesla to change the roads.

Identify and avoid naysayers

Do your homework on the industries and companies that you think you can best convince that the benefits of your entry are easily visible and profitable. Have they adapted quickly to changes in the IT infrastructure or have they been slow to respond? Have they been among the first to invest in emerging technologies or, like sheep, have they waited and followed the herd? There’s a hilarious TV ad capturing the frustration of dealing with naysayers, featuring notorious curmudgeon Larry David, creator of “Seinfeld” and “Curb Your Enthusiasm.” He’s in a bad mood. And so he was included in a clever ad campaign as the “guy I hate him” throughout the story: when he turned up the wheel; Fork; the toilet; coffee; democracy; The light bulb; travel to the moon; electric vehicles. The campaign, created by cryptocurrency company FTX, is marked by the slogan “Don’t be like Larry.”

Yes, we have our fair share of detractors in technology and other industries where new approaches are introduced to win the day. The detractors resist seeing the world in a different way: they are those who do not see the possibilities offered by a new solution. They threaten business progress and can even hasten an organization’s decline.

Mike Palmer is CEO of Sigma computing.


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