[Editor’s note: This is the third of three excerpts from The Billion Dollar Byte by D. Justhy, a new book that equips companies with the tools to leverage Big Data to drive “Good Profit” and adopt a whole new business model, one that is apt for the Digital Age. Global Trade Daily thanks the author and his publisher.]

There are many ways companies can employ big data to produce good profit. There are at least six major ways that good profit can be generated with emerging data technologies:

increased revenues, reduced expenditures, profitable compliance, improved business valuation, attraction and retention of talent, and global contribution.

Increased revenue is the most direct method of increasing profits. Big data allows enterprises to better understand their own businesses and industries through the use of high-quality analytics. Data and the insights it yields can help companies increase sales, enhance revenue streams, and improve product offerings. Increased revenues are a function of the business doing better business. This is especially true when companies employ person-centric analytics to better understand the market, allowing them to maximize revenue by appealing to the right people.

The second most direct way of increasing profits is by reducing expenditures. Data collected on business processes can be used to identify and systematically eliminate inefficiencies. Methods such as process analytics are perfect for this job. Improved efficiency that leads to lower expenditures is a direct way to turn hard-earned revenues into captured profits.

The third way companies can use data to increase profits is by engaging in profitable compliance. Compliance is a major cost. Companies can lose big if they face a fine or are publicly exposed as noncompliant on issues of financial risk, safety, or corporate responsibility. Companies must ensure that all business processes are compliant with regulations. There are often many ways in which companies can comply with regulations. Profitable compliance is when companies find the most efficient and low-cost methods of honestly and fully meeting compliance. Because compliance is managed through business processes, companies have data about their compliance programs that can be used to streamline those processes. Companies should ensure that data and analytics are an integral part of their auditing and compliance programs.

The fourth way in which companies can profit from big data is through a massive increase in their business valuation. Companies achieve higher valuations by putting an emphasis on the pursuit of economic value. Value creation is the pursuit of all enterprises. All business processes should focus on value creation. There are, of course, innumerable ways to do this with big data, such as creating person-centric data practices.

Creating value is not just about what companies do. They must also consider what not to do. Initiatives that don’t create value should not be pursued. Companies that want to increase their valuation should abandon activities that don’t create economic value. These no- and low-value initiatives can be identified through data analytics.

The fifth way of creating profit with big data is by attracting and retaining talent. To do this, companies must create an ecosystem that not only attracts good people, but also one that encourages them to stay by offering rewards, growth potential, and a good company culture. Companies must reconsider how they manage people. Again, data is your friend here. Companies should employ person-centric analytics for talent management.

Above all, invest in the datapreneur. Companies need people with leadership as well as technical abilities in a variety of roles. Search for ways to train and develop staff to become your datapreneurs. All key people in a company, no matter their role, should receive continuous and relevant development throughout their career.

The sixth way that companies can increase good profits through big data is by contributing to the world. This is what makes profits good. When what a company does contributes to the betterment of the world, the profits it produces are good profits. This positive contribution doesn’t have to be “synthetically” philanthropic. Companies profit when they truly meet people’s wants and needs. This betters the world. And when data is used, it is an example of data bettering the world. This happens all of the time in the age of big data. For example, when a tech company supplies certain analytics to an industry, this betters all of society by contributing to the economy. It is also true that the companies using those analytics are now profiting more, as well as contributing more to society.

This sixth and final method of increasing profits is particularly important because it underpins the way in which profit for companies becomes good profit for societies. This happens all the time and is a function of the kind of strong free-market economy for which Charles Koch and others, including myself, advocate.

Justhy Deva Prasad, M.B.A., “D. Justhy,” is the Chief Data Partner at Claritysquare, a global technology firm that helps Fortune 500 clients around the globe transition to the digital age by leveraging data to reduce costs, recapture lost value, and generate new revenue. He is the author of “The Billion Dollar Byte” (Morgan James, January 2018).

[Editor’s note: This is the second of three excerpts from The Billion Dollar Byte by D. Justhy, a new book that equips companies with the tools to leverage Big Data to drive “Good Profit” and adopt a whole new business model, one that is apt for the Digital Age. Global Trade Daily thanks the author and his publisher.]

As large traditional companies wake up to the age of big data, data strategy has become a matter of boardroom-level importance. Today’s boardrooms take data strategy every bit as seriously as business strategy. This was never the case before. Traditional companies are seeing the Digital Native companies racking up massive valuations, ten times that achieved by the most successful traditional companies, and they’re doing it with data.

Traditional companies want in on the action. Increasingly, traditional companies are developing digital business models in the boardroom. They understand data technologies can no longer be ignored, and that means integrating them into the business model. Failure to do so means ultimate failure. Since the 1950s, 88 percent of Fortune 500 companies have disappeared. This is because they fail to remain relevant as the business environment changes. In many cases, these companies thrived in the Industrial Age but failed in the Digital Age. Companies and boards that lack the capability or capacity to make use of big data and analytics are being left behind. More will fail until the last men standing are the Digital Natives and the traditional companies that went digital.

Traditional companies don’t necessarily need to become digital companies, but they should be relevant in the Digital Age. A traditional bank is unlikely to ever look like Twitter, but today, they all offer online banking. Some, such as Capital One, offer fully online services and don’t operate many, if any, physical banks—only ATMs, kiosks, and robust digital offerings.

All of this online activity creates new data trails that are assets. Ignoring data is ignoring assets. Boards wouldn’t dare ignore other assets that can increase shareholder returns—so why keep ignoring data?

The big decisions around company data cannot be made by company techies. There are executive-level decisions to be made about how to allocate resources, build up technology capabilities, and compete in a Digital Age. Traditional companies have to make investments in analytics, and make this part of their business processes. This must be done from the top; it cannot be left to the techies in the IT department. The people who use the emerging technologies are great at their jobs, but the boardroom is where executive-level decisions are made.

Boardrooms need to do at least three things that techies cannot do in order to use data to return greater value to shareholders. First, they need to extend the life cycle of the data value chain. Traditionally, data consumption and reporting were the last stage of the data value chain. Companies would collect data, process it, and only then use it for value-generating reporting and analytics. This paradigm no longer works. Emerging technologies allow companies to derive value from data at every stage of the life cycle. Companies today need to start utilizing and consuming data from the moment it is created to long after it is archived.

For example, companies should now start utilizing social media data the very instant that it is generated. The data can be used in real time to create value by adjusting pricing, giving targeted promotional offers, and even realigning the social media campaign itself. The data can be used as a capability to offer better services. Consider how Uber uses surge pricing to bring more drivers to underserved areas. Traditional companies can do the same type of things with their data without having to go entirely digital.

The second thing boardrooms must do is oversee the use of big-data technologies in auditing. Auditing is complicated and resource intensive. Large companies may spend several months per year struggling to complete internal and external audits. Data technologies can make auditing easier and more efficient, mitigate risk surrounding auditing, and create new value by better utilizing business process data for auditing. This is because new technologies allow companies to better see what’s going on and unlock new insights into the auditing process and the information gleaned from it.

The third responsibility boards have regarding data is to ensure that data is producing maximum value for shareholders. This is literally the role of companies, as board members are required to return value to shareholders above all else. Failure to use data to do so is a failure of their first duty. Data can unlock new capabilities and be leveraged as an asset to create value for shareholders. Many companies already do this, but it can be done to a much greater degree, especially by traditional companies with legacy cultures. The Digital Natives had the advantage of growing up in a digital environment; their processes were adapted to the environment. Traditional companies didn’t have this luxury. They have to be active in creating new rules, culture, and processes that bring their companies into the Digital Age. They were not born adapted to the environment, but they must become so now.

For this to happen, boards must take on a greater role regarding data and be proactive in developing their data strategy. Previously, companies made reactionary decisions about data. They used reports, which might have been months or even years out of date, to make decisions about future actions. This is outmoded and even irresponsible to an extent. New technologies allow data to be used in “real and right” time, and it must be managed as such.

Things move so fast now that boardrooms can start to feel like boiler rooms. It is only by using data as a capability and asset, with the help of emerging technologies, that boards can keep up. There is no other way to assimilate, process, and make sense of data in real time. Traditional companies have never before had to operate in this way. The transition can only be made if boards take an active role. This isn’t a job for the techies; it’s a job for the C-suite.

Justhy Deva Prasad, M.B.A., “D. Justhy,” is the Chief Data Partner at Claritysquare, a global technology firm that helps Fortune 500 clients around the globe transition to the digital age by leveraging data to reduce costs, recapture lost value, and generate new revenue. He is the author of “The Billion Dollar Byte” (Morgan James, January 2018).

[Editor’s note: This is the first of three excerpts from The Billion Dollar Byte by D. Justhy, a new book that equips companies with the tools to leverage Big Data to drive “Good Profit” and adopt a whole new business model, one that is apt for the Digital Age. Global Trade Daily thanks the author and his publisher.]

Many traditional companies are already making big investments in big data. Research firm IDC predicts that annual spending will reach $48.6 billion in 2019, at a compound annual growth rate of 23 percent. The C-suites of large companies have millions or billions of dollars to invest in IT and, increasingly, they are investing in developing a data strategy. For most executives, this means making investments in new technology tools. They want the “Next Big Thing” they’ve heard so much about.

This is where they run into problems, with a high probability of failure.

Executives making decisions on technology spending are inundated with options. In all technology markets, including data, there are hundreds of vendors making similar tools to solve similar problems. It can be hard to tell which are better. Company executives often cannot differentiate one from another because vendors create products and services for the marketplace, not for one’s specific enterprise. It’s the job of the executives—not the vendors—to make them work successfully in their organization.

The C-suites of traditional companies are not adequately equipped to discern hype from real value. They don’t have the luxury of time and resources to comprehensively assess their options in order to make decisions about where to allocate IT budgets, what outlays to make, and which tools to acquire and adopt. For the most part, this is done as a reaction to market “chatter,” or “qualitative assumptions,” at best. There is no scientific and certain method to doing so.

This can make executives very skeptical of not only the tools and technologies, but also of the concept of big data itself, especially if they have been around for a few decades. The market is full of noise and hype. Executives don’t know which companies to trust when there are so many vendors, sometimes ones with as big or even bigger company valuations. They don’t know which tools to buy because they all look the same but promise more. They have nothing to go on but the word of markets and salespeople. Of course, the techies get excited by the very sound of it. It’s both a blessing and a curse, unless you learn how to make it the former.

These decisions can cause paralyzing anxiety for decision makers. Millions—sometimes, billions—of dollars in outlays are on the line. Given this situation, executives become worried and even jaded. Every day there is a new start-up purporting to offer the next big thing in technology. This can make even the most enthusiastic and forward-thinking executives skeptical about the whole endeavor. They begin to wonder how they can ever make an appropriate decision, and simply hope someone they trust can make the decision for them. Which tools are the best? Eventually they may wonder, Do I need any of this at all? Isn’t this just hype?

The answer is no, it is not all hype.

The truth is that many big-data technology companies are putting out good products. In fact, most technology companies that stick around for any period of time are creating good technology offerings. They wouldn’t survive the market otherwise. Many of these companies got started in Silicon Valley and are founded and staffed by the best technologists available. Some are even funded by the National Security Agency in the United States. Your data company might well have had a role to play in helping to find Osama bin Laden. These are reputable companies. If you have checked them out, you don’t need to worry; they will deliver the goods.

But that doesn’t mean that you need all of the tools and technologies available in the marketplace.

Big data isn’t about tools and technologies alone. It’s about how you utilize the data that is relevant to your business model in order to maximize enterprise value exponentially through improved and better business processes. Ultimately, it’s all about having a better life on the planet, improving the process of life itself.

Rather than focusing on what tools and technologies to buy from a “shopping list,” executives need to pause and ask, How can data create value for my business? Only then should they start looking at what tools and technologies to invest in. Most companies will find that they don’t need many of the shiny, new products being hawked by start-ups. Many companies will find that they already have quite a few of the tools they need; they just need to be using them in the right ways to create value.

The thing to remember is that big data is still just data; only, it is, as the name implies, data gone bigger. Nothing has fundamentally changed in the way we handle data—only the amount of data handled, the variety of data based on the potential sources, and the velocity of data streams that are relevant to the business. These things matter. They allow us to get more value out of data. They open up new possibilities for valuable insights, but the building blocks are the same. The difference is fundamentally one of scale, not type (scale in relative terms depending on your business model).

Imagine you are building a Lego house when suddenly you realize you could piece together more houses and make a Lego city. If you were poorly organized to begin with, more tools will only amplify your inefficiency. On the other hand, if you were well organized and disciplined in the process of sourcing, organizing, and putting the blocks together for building a house, tools will probably make you more efficient and enable you to build a city using similar methods but with better tools. Besides, the multiplication driver is not more tools. For the most part, you just need more blocks—especially if you have been well organized and efficient in the process of building a house to begin with. The process of sourcing the increased number of blocks and organizing them for use, though, now needs to take into account the increased scale, velocity, and probably variety, if appropriate for building a Lego city.

Big data is the same. Companies are still just acquiring, processing, and consuming data—only now there is much, much more of it. Remember that it is a realization that we can do more with our data with currently available tools and technologies.

Companies don’t need to look for the latest and greatest thing; they need to look for what works for them. Often, this will be a tool or a technology that is relevant and well understood, and which can be managed within their organization without crippling people.

Companies spend too much time worrying about tools and technologies for acquiring and processing data. The tools one uses are less important than what one achieves with them. Companies need to put the emphasis back on the basics of a process. The data-strategy setup does not need to provide a host of flashy new tools, but it should support the business processes and the business model.

Often—not always, but often—this means sticking with what you know and do. The only difference is doing it well.

Justhy Deva Prasad, M.B.A., “D. Justhy,” is the Chief Data Partner at Claritysquare, a global technology firm that helps Fortune 500 clients around the globe transition to the digital age by leveraging data to reduce costs, recapture lost value, and generate new revenue. He is the author of “The Billion Dollar Byte” (Morgan James, January 2018).