Taking The Sting Out Of Dealing With Outdated Custom Code

Carl Dubler

Part 2 in the “Journey to Intelligent ERP” series

It seems that many IT folks would rather have a tooth extracted than come to grips with their custom code.

This is understandable since they are often the custodians of an ERP system that’s been tweaked and adapted over the course of a decade or two. With no clear insight into the scale of the problem, dealing with custom code can seem daunting. Where to begin? Hence, they put off their ERP modernization projects. Meanwhile, the business suffers from its inability to increase agility, just as IT continues to be stuck with overly complex operations.

Adapting incompatible code doesn’t have to hurt

However, evaluating and adapting custom code can be less intimidating than it might seem. Here’s an example: One SAP customer, preparing to upgrade to a next-generation ERP solution, discovered tens of thousands of custom objects and source code items within its ERP system. IT staff were apprehensive about how much work would be involved. And when a readiness-check tool identified more than 4,000 objects incompatible with the new solution, this seemed like an impossible task.

However, using the tool, the team found that they could overcome about half of those problems with a simple fix to the material number field length. About a quarter of the issues were fixed with database views in the new ERP application that mimic the existing ERP structure. The rest required some changes to the code to account for new data models and performance improvements.

Making modernization a key strategic initiative

A key factor that helped motivate the IT team to deal with custom code adaption was the engagement of the CIO, who made the project a strategic priority. For this leading European manufacturer, a high-end brand with worldwide retail distribution, staying current with technology is intrinsic to its business model.

While the team was initially dismayed by the report of thousands of required adaptions, they actually finished this part of the project in a matter of weeks and quickly moved on to the main objective. Now, with a next-generation, intelligent ERP solution in place, the company is on its way toward streamlined processes, faster and better-informed decision-making, and improved business agility. It all began by taking a simple inventory of custom code.

Ensuring custom-code hygiene going forward

Like visiting the dentist, custom-code hygiene is less scary the more frequently you do it. By continually assessing custom code and avoiding it where possible, the next upgrade or innovation will be a lot easier.

A number of valuable tools are available to help you establish a healthy regimen. Most ERP solutions offer usage and procedure logging functionality that logs the use of custom code over time. Tools like these show you which custom code is critical for operations to help you make informed decisions about what needs to stay and where you should return to standard. Recent figures indicate that 65% of custom code objects are no longer in use and only 23% support critical business processes.*

What if standard functionality still isn’t enough?

When you do identify code that is no longer necessary, there are even custom code lifecycle management tools that help with decommissioning. However, if you still need custom development, consider doing that in a cloud development platform. This keeps future customizations out of the way when updates are done, makes them more useful across cloud and on-premise deployments, and allows you to take advantage of the latest technologies and commoditized infrastructure.

In the next blog, we’ll look at how the cloud can accelerate your journey to intelligent ERP. In the meantime, read more here about the SAP Readiness Check tool for SAP S/4HANA. You can also learn more by reading the SAP S/4HANA Journey Guide. 

* Based on continuous quality check data for solution transition assessment and custom code services


Carl Dubler

About Carl Dubler

Carl Dubler is a senior director of Product Marketing for SAP S/4HANA. With an IT career stretching back to the late 1980s, he has done nearly every role in the business. In his ten years at SAP, he also managed SAP’s first commercially available cloud product and first cloud product on SAP HANA.

CRM In Today’s Ecosystem: What CIOs Need To Know

Riaz Faride

Companies these days usually choose to position themselves as an entity with purpose – a purpose reflecting customer-centricity beyond profit. They develop and commercialize their products accordingly, whether the products are architecturally interdependent or modular. In addition to market share, profitability, and earnings-per-share growth, measuring advocacy as a metric is trending, since it can be an indicator of positive customer experience. It is equally important as measuring satisfaction.

A customer relationship management (CRM) solution is an obvious choice for today’s leaders due to its capabilities of tracking the customer base and their experiences by channels and touch points. Combining CRM with a business intelligence (BI) tool adds significant value since it draws data from multiple sources and provides a business-focused analysis.

Leaping ahead with sophisticated functionality

Today’s CRM solutions are no longer limited to contact management, campaign management, lead management, deals and tasks, email and social media tracking; CRM has leaped beyond its traditional boundaries. Native capabilities or implementation readiness with marketing automation, online reputation management (ORM), and voice of the customer (VoC) solutions are some key options available for consideration by today’s leaders. This flexibility allows businesses to build relationships with unidentified viewers and their influencers, leads, customers, and even advocates of the products!

From a functionality perspective, selecting a CRM solution encompasses many criteria. These include the ability to mine, consolidate, and analyze data for better insights; scalability; high availability; intuitive and process-driven interface; mobile support, spanning the most commonly used device sizes and types; and operating systems. In this age, the need for responsive or adaptive mobile sites is paramount. All these factors are reflected through the architecture, features, and adaptability of a CRM solution. Thus, software lifecycle management and product roadmap should be evaluated during selection of a CRM solution.

Incorporating the latest technologies

CRM is being impacted by contextual customer service through chatbots. Predictive analysis of historical and live data through machine learning has influenced CRM, as well. Ditto virtual reality (VR), which allows customers to interact through software, and the Internet of Things (IoT), which greatly facilitates analysis of customers through real-time data from devices. Inversely, CRM has a meaningful impact on real-time personalization and connected experience.

CRM helps businesses look at their markets through different lenses. This allows them to offer their products that serve the “purpose” of their respective customer base: the task the customers are trying to accomplish or a problem or issue they want to resolve.

Businesses with mature products can leverage CRM and its extensions to define a winning strategy and help them determine success and failure criteria. CRM is also useful during the early phases of a company’s or product’s life, or when the future is unknown and the competitive landscape is changing. The mix of these two use cases is very common and dictates the need for a flexible, user-friendly, scalable CRM solution.

Protecting privacy and complying with regulatory mandates

While CRM in the cloud is gaining popularity exponentially, some decision-makers are still concerned about security and the privacy of customers, leads, and uncategorized users. This is understandable given the importance of compliance with data processing and privacy directives across multiple jurisdictions. In addition, IT leaders need to protect systems and data against vulnerabilities and ensure business continuity. Cloud providers can play an important consultative role during CRM planning and implementation – for example, recommending or providing managed services.

Learn more

For more information about solutions supporting customer engagement and commerce, and fully integrating marketing, commerce, sales, and service, please visit SAP Hybris.


Riaz Faride

About Riaz Faride

Riaz Faride joined SAP in 2017. Prior to this, he worked in the retail industry and had an extensive history in delivering high-value omnichannel projects. Throughout his career, Riaz has been exposed to all avenues of e-commerce, making him a subject matter expert. As a thought leader in his field, Riaz is a mentor for a number of professionals in e-commerce, omnichannel, and project management. He values ongoing learning and growth in both technical and non-technical fields.

Seven Questions To Ask Before Hiring A Managed Service Provider

Daniel Newman

There’s a lot to keep track of in today’s IT departments, and many businesses are hiring managed service providers (MSPs) to help lessen the load. But are they really necessary? And what value do they really bring to the business table? If you’re currently considering partnering with an MSP to support your company’s digital transformation, be sure to ask the following questions before signing on the dotted line.

How does this MSP help drive my business goals?

Face it: Technology is sexy. There’s a huge pressure on all businesses right now to adopt every new fad and fashion that comes along in the name of tech advancement. But at the end of the day, every investment you make in technology needs to support your specific business goals and vision to be worth the cost associated with it. Before choosing an MSP, be sure to outline your short- and long-term business objectives to ensure that the chosen MSP will help you grow both.

Is the ROI substantial?

Some companies see the immediate cost savings associated with MSPs and assume an improved bottom line is enough. I’d argue that’s only part of the equation. Lots of MSPs can save you money in the short term. But if they can’t grow with you—innovate alongside you—and help you grow in your own way, they may not be worth the investment. Be sure to research how the MSP will help you innovate and advance your business processes—creating more efficient workflows, etc.—before making a commitment.

How will the MSP help optimize, rather than just clean up our mess?

Do you have a tech mess on your hands right now? Is that what’s driving you to seek out an MSP? If so, you aren’t alone. The sheer overwhelming and exhausting task of working through the digital transformation is enough to make any business cry “uncle!” and reach out for help. Still, taking a mess off your IT team’s hands is not enough. Your MSP should be helping you make more—do more—achieve more—than you’re able to do on your own. That’s the benefit of technology—cloud—managed as a service (aaS).

How compatible is it in the long term?

The MSP you choose needs to be compatible now, but also in the long term. It needs to offer bigger and better services than what you currently require because someday you’ll be bigger and better yourself. Choosing a small company isn’t bad. But they need to have a big vision—and one you can count on into the future.

How innovative is the MSP team?

You know how fast things are moving in the digital landscape. As important as it is for our own companies to embrace continuous learning of new trends and innovations in the marketplace, it’s equally or more important for our MSPs. When we choose an MSP, we’re relying on them to take the reins on a chosen tech service. We’re counting on them to be up on changes, improvements, enhancements, and service options available in the greater tech community. We need them to be in-the-know—not just content with the services they currently offer. And, we need them to keep us informed of those new services and innovations as soon as they become available so we can start taking advantage of them if they’re a good fit.

Who is supporting me? 

There is nothing worse than partnering with an MSP, only to find that they have no help desk, their email support is a black hole, and their chatbot is always frozen. Before you partner with an MSP, be sure to understand exactly who will be supporting you. Will it be a team of trained engineers available 24/7? A team of chatbots? A call center with limited hours? How long does it take to respond or fix an issue? If possible, get references and ask them how the support has been. Don’t take the MSP’s word for it. Your company is too valuable not to do your due diligence.

What kind of SLA is available?

Last but not least, make sure you’re 100% on board with your MSP’s service-level agreement (SLA). Is it flexible? Does it hold the MSP accountable for support—in a timely manner? Does it allow you to grow, or keep you locked into a certain level of support? Or will you need a new MSP once you expand? It’s important to fully understand the finest details of the SLA before choosing your MSP partner.

Tech trends don’t become trends unless they hold at least some inherent value. MSPs can be incredibly valuable to your business if utilized well. But as with any trend, it’s possible to fall for the lure of the bandwagon, rather than following your true business goals. The questions above will help guide you in making the right—smart—MSP decision.

Additional Articles on This Topic:

This article originally appeared on Future of Work.


Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

Hack the CIO

By Thomas Saueressig, Timo Elliott, Sam Yen, and Bennett Voyles

For nerds, the weeks right before finals are a Cinderella moment. Suddenly they’re stars. Pocket protectors are fashionable; people find their jokes a whole lot funnier; Dungeons & Dragons sounds cool.

Many CIOs are enjoying this kind of moment now, as companies everywhere face the business equivalent of a final exam for a vital class they have managed to mostly avoid so far: digital transformation.

But as always, there is a limit to nerdy magic. No matter how helpful CIOs try to be, their classmates still won’t pass if they don’t learn the material. With IT increasingly central to every business—from the customer experience to the offering to the business model itself—we all need to start thinking like CIOs.

Pass the digital transformation exam, and you probably have a bright future ahead. A recent SAP-Oxford Economics study of 3,100 organizations in a variety of industries across 17 countries found that the companies that have taken the lead in digital transformation earn higher profits and revenues and have more competitive differentiation than their peers. They also expect 23% more revenue growth from their digital initiatives over the next two years—an estimate 2.5 to 4 times larger than the average company’s.

But the market is grading on a steep curve: this same SAP-Oxford study found that only 3% have completed some degree of digital transformation across their organization. Other surveys also suggest that most companies won’t be graduating anytime soon: in one recent survey of 450 heads of digital transformation for enterprises in the United States, United Kingdom, France, and Germany by technology company Couchbase, 90% agreed that most digital projects fail to meet expectations and deliver only incremental improvements. Worse: over half (54%) believe that organizations that don’t succeed with their transformation project will fail or be absorbed by a savvier competitor within four years.

Companies that are making the grade understand that unlike earlier technical advances, digital transformation doesn’t just support the business, it’s the future of the business. That’s why 60% of digital leading companies have entrusted the leadership of their transformation to their CIO, and that’s why experts say businesspeople must do more than have a vague understanding of the technology. They must also master a way of thinking and looking at business challenges that is unfamiliar to most people outside the IT department.

In other words, if you don’t think like a CIO yet, now is a very good time to learn.

However, given that you probably don’t have a spare 15 years to learn what your CIO knows, we asked the experts what makes CIO thinking distinctive. Here are the top eight mind hacks.

1. Think in Systems

A lot of businesspeople are used to seeing their organization as a series of loosely joined silos. But in the world of digital business, everything is part of a larger system.

CIOs have known for a long time that smart processes win. Whether they were installing enterprise resource planning systems or working with the business to imagine the customer’s journey, they always had to think in holistic ways that crossed traditional departmental, functional, and operational boundaries.

Unlike other business leaders, CIOs spend their careers looking across systems. Why did our supply chain go down? How can we support this new business initiative beyond a single department or function? Now supported by end-to-end process methodologies such as design thinking, good CIOs have developed a way of looking at the company that can lead to radical simplifications that can reduce cost and improve performance at the same time.

They are also used to thinking beyond temporal boundaries. “This idea that the power of technology doubles every two years means that as you’re planning ahead you can’t think in terms of a linear process, you have to think in terms of huge jumps,” says Jay Ferro, CIO of TransPerfect, a New York–based global translation firm.

No wonder the SAP-Oxford transformation study found that one of the values transformational leaders shared was a tendency to look beyond silos and view the digital transformation as a company-wide initiative.

This will come in handy because in digital transformation, not only do business processes evolve but the company’s entire value proposition changes, says Jeanne Ross, principal research scientist at the Center for Information Systems Research at the Massachusetts Institute of Technology (MIT). “It either already has or it’s going to, because digital technologies make things possible that weren’t possible before,” she explains.

2. Work in Diverse Teams

When it comes to large projects, CIOs have always needed input from a diverse collection of businesspeople to be successful. The best have developed ways to convince and cajole reluctant participants to come to the table. They seek out technology enthusiasts in the business and those who are respected by their peers to help build passion and commitment among the halfhearted.

Digital transformation amps up the urgency for building diverse teams even further. “A small, focused group simply won’t have the same breadth of perspective as a team that includes a salesperson and a service person and a development person, as well as an IT person,” says Ross.

At Lenovo, the global technology giant, many of these cross-functional teams become so used to working together that it’s hard to tell where each member originally belonged: “You can’t tell who is business or IT; you can’t tell who is product, IT, or design,” says the company’s CIO, Arthur Hu.

One interesting corollary of this trend toward broader teamwork is that talent is a priority among digital leaders: they spend more on training their employees and partners than ordinary companies, as well as on hiring the people they need, according to the SAP-Oxford Economics survey. They’re also already being rewarded for their faith in their teams: 71% of leaders say that their successful digital transformation has made it easier for them to attract and retain talent, and 64% say that their employees are now more engaged than they were before the transformation.

3. Become a Consultant

Good CIOs have long needed to be internal consultants to the business. Ever since technology moved out of the glasshouse and onto employees’ desks, CIOs have not only needed a deep understanding of the goals of a given project but also to make sure that the project didn’t stray from those goals, even after the businesspeople who had ordered the project went back to their day jobs. “Businesspeople didn’t really need to get into the details of what IT was really doing,” recalls Ferro. “They just had a set of demands and said, ‘Hey, IT, go do that.’”

Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants.

But that was then. Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants. “If you’re building a house, you don’t just disappear for six months and come back and go, ‘Oh, it looks pretty good,’” says Ferro. “You’re on that work site constantly and all of a sudden you’re looking at something, going, ‘Well, that looked really good on the blueprint, not sure it makes sense in reality. Let’s move that over six feet.’ Or, ‘I don’t know if I like that anymore.’ It’s really not much different in application development or for IT or technical projects, where on paper it looked really good and three weeks in, in that second sprint, you’re going, ‘Oh, now that I look at it, that’s really stupid.’”

4. Learn Horizontal Leadership

CIOs have always needed the ability to educate and influence other leaders that they don’t directly control. For major IT projects to be successful, they need other leaders to contribute budget, time, and resources from multiple areas of the business.

It’s a kind of horizontal leadership that will become critical for businesspeople to acquire in digital transformation. “The leadership role becomes one much more of coaching others across the organization—encouraging people to be creative, making sure everybody knows how to use data well,” Ross says.

In this team-based environment, having all the answers becomes less important. “It used to be that the best business executives and leaders had the best answers. Today that is no longer the case,” observes Gary Cokins, a technology consultant who focuses on analytics-based performance management. “Increasingly, it’s the executives and leaders who ask the best questions. There is too much volatility and uncertainty for them to rely on their intuition or past experiences.”

Many experts expect this trend to continue as the confluence of automation and data keeps chipping away at the organizational pyramid. “Hierarchical, command-and-control leadership will become obsolete,” says Edward Hess, professor of business administration and Batten executive-in-residence at the Darden School of Business at the University of Virginia. “Flatter, distributive leadership via teams will become the dominant structure.”

5. Understand Process Design

When business processes were simpler, IT could analyze the process and improve it without input from the business. But today many processes are triggered on the fly by the customer, making a seamless customer experience more difficult to build without the benefit of a larger, multifunctional team. In a highly digitalized organization like Amazon, which releases thousands of new software programs each year, IT can no longer do it all.

While businesspeople aren’t expected to start coding, their involvement in process design is crucial. One of the techniques that many organizations have adopted to help IT and businesspeople visualize business processes together is design thinking (for more on design thinking techniques, see “A Cult of Creation“).

Customers aren’t the only ones who benefit from better processes. Among the 100 companies the SAP-Oxford Economics researchers have identified as digital leaders, two-thirds say that they are making their employees’ lives easier by eliminating process roadblocks that interfere with their ability to do their jobs. Ninety percent of leaders surveyed expect to see value from these projects in the next two years alone.

6. Learn to Keep Learning

The ability to learn and keep learning has been a part of IT from the start. Since the first mainframes in the 1950s, technologists have understood that they need to keep reinventing themselves and their skills to adapt to the changes around them.

Now that’s starting to become part of other job descriptions too. Many companies are investing in teaching their employees new digital skills. One South American auto products company, for example, has created a custom-education institute that trained 20,000 employees and partner-employees in 2016. In addition to training current staff, many leading digital companies are also hiring new employees and creating new roles, such as a chief robotics officer, to support their digital transformation efforts.

Nicolas van Zeebroeck, professor of information systems and digital business innovation at the Solvay Brussels School of Economics and Management at the Free University of Brussels, says that he expects the ability to learn quickly will remain crucial. “If I had to think of one critical skill,” he explains, “I would have to say it’s the ability to learn and keep learning—the ability to challenge the status quo and question what you take for granted.”

7. Fail Smarter

Traditionally, CIOs tended to be good at thinking through tests that would allow the company to experiment with new technology without risking the entire network.

This is another unfamiliar skill that smart managers are trying to pick up. “There’s a lot of trial and error in the best companies right now,” notes MIT’s Ross. But there’s a catch, she adds. “Most companies aren’t designed for trial and error—they’re trying to avoid an error,” she says.

To learn how to do it better, take your lead from IT, where many people have already learned to work in small, innovative teams that use agile development principles, advises Ross.

For example, business managers must learn how to think in terms of a minimum viable product: build a simple version of what you have in mind, test it, and if it works start building. You don’t build the whole thing at once anymore.… It’s really important to build things incrementally,” Ross says.

Flexibility and the ability to capitalize on accidental discoveries during experimentation are more important than having a concrete project plan, says Ross. At Spotify, the music service, and CarMax, the used-car retailer, change is driven not from the center but from small teams that have developed something new. “The thing you have to get comfortable with is not having the formalized plan that we would have traditionally relied on, because as soon as you insist on that, you limit your ability to keep learning,” Ross warns.

8. Understand the True Cost—and Speed—of Data

Gut instincts have never had much to do with being a CIO; now they should have less to do with being an ordinary manager as well, as data becomes more important.

As part of that calculation, businesspeople must have the ability to analyze the value of the data that they seek. “You’ll need to apply a pinch of knowledge salt to your data,” advises Solvay’s van Zeebroeck. “What really matters is the ability not just to tap into data but to see what is behind the data. Is it a fair representation? Is it impartial?”

Increasingly, businesspeople will need to do their analysis in real time, just as CIOs have always had to manage live systems and processes. Moving toward real-time reports and away from paper-based decisions increases accuracy and effectiveness—and leaves less time for long meetings and PowerPoint presentations (let us all rejoice).

Not Every CIO Is Ready

Of course, not all CIOs are ready for these changes. Just as high school has a lot of false positives—genius nerds who turn out to be merely nearsighted—so there are many CIOs who aren’t good role models for transformation.

Success as a CIO these days requires more than delivering near-perfect uptime, says Lenovo’s Hu. You need to be able to understand the business as well. Some CIOs simply don’t have all the business skills that are needed to succeed in the transformation. Others lack the internal clout: a 2016 KPMG study found that only 34% of CIOs report directly to the CEO.

This lack of a strategic perspective is holding back digital transformation at many organizations. They approach digital transformation as a cool, one-off project: we’re going to put this new mobile app in place and we’re done. But that’s not a systematic approach; it’s an island of innovation that doesn’t join up with the other islands of innovation. In the longer term, this kind of development creates more problems than it fixes.

Such organizations are not building in the capacity for change; they’re trying to get away with just doing it once rather than thinking about how they’re going to use digitalization as a means to constantly experiment and become a better company over the long term.

As a result, in some companies, the most interesting tech developments are happening despite IT, not because of it. “There’s an alarming digital divide within many companies. Marketers are developing nimble software to give customers an engaging, personalized experience, while IT departments remain focused on the legacy infrastructure. The front and back ends aren’t working together, resulting in appealing web sites and apps that don’t quite deliver,” writes George Colony, founder, chairman, and CEO of Forrester Research, in the MIT Sloan Management Review.

Thanks to cloud computing and easier development tools, many departments are developing on their own, without IT’s support. These days, anybody with a credit card can do it.

Traditionally, IT departments looked askance at these kinds of do-it-yourself shadow IT programs, but that’s changing. Ferro, for one, says that it’s better to look at those teams not as rogue groups but as people who are trying to help. “It’s less about ‘Hey, something’s escaped,’ and more about ‘No, we just actually grew our capacity and grew our ability to innovate,’” he explains.

“I don’t like the term ‘shadow IT,’” agrees Lenovo’s Hu. “I think it’s an artifact of a very traditional CIO team. If you think of it as shadow IT, you’re out of step with reality,” he says.

The reality today is that a company needs both a strong IT department and strong digital capacities outside its IT department. If the relationship is good, the CIO and IT become valuable allies in helping businesspeople add digital capabilities without disrupting or duplicating existing IT infrastructure.

If a company already has strong digital capacities, it should be able to move forward quickly, according to Ross. But many companies are still playing catch-up and aren’t even ready to begin transforming, as the SAP-Oxford Economics survey shows.

For enterprises where business and IT are unable to get their collective act together, Ross predicts that the next few years will be rough. “I think these companies ought to panic,” she says. D!

About the Authors

Thomas Saueressig is Chief Information Officer at SAP.

Timo Elliott is an Innovation Evangelist at SAP.

Sam Yen is Chief Design Officer at SAP and Managing Director of SAP Labs.

Bennett Voyles is a Berlin-based business writer.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


The Differences Between Machine Learning And Predictive Analytics

Shaily Kumar

Many people are confused about the specifics of machine learning and predictive analytics. Although they are both centered on efficient data processing, there are many differences.

Machine learning

Machine learning is a method of computational learning underlying most artificial intelligence (AI) applications. In ML, systems or algorithms improve themselves through data experience without relying on explicit programming. ML algorithms are wide-ranging tools capable of carrying out predictions while simultaneously learning from over trillions of observations.

Machine learning is considered a modern-day extension of predictive analytics. Efficient pattern recognition and self-learning are the backbones of ML models, which automatically evolve based on changing patterns in order to enable appropriate actions.

Many companies today depend on machine learning algorithms to better understand their clients and potential revenue opportunities. Hundreds of existing and newly developed machine learning algorithms are applied to derive high-end predictions that guide real-time decisions with less reliance on human intervention.

Business application of machine learning: employee satisfaction

One common, uncomplicated, yet successful business application of machine learning is measuring real-time employee satisfaction.

Machine learning applications can be highly complex, but one that’s both simple and very useful for business is a machine learning algorithm that compares employee satisfaction ratings to salaries. Instead of plotting a predictive satisfaction curve against salary figures for various employees, as predictive analytics would suggest, the algorithm assimilates huge amounts of random training data upon entry, and the prediction results are affected by any added training data to produce real-time accuracy and more helpful predictions.

This machine learning algorithm employs self-learning and automated recalibration in response to pattern changes in the training data, making machine learning more reliable for real-time predictions than other AI concepts. Repeatedly increasing or updating the bulk of training data guarantees better predictions.

Machine learning can also be implemented in image classification and facial recognition with deep learning and neural network techniques.

Predictive analytics

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. Basic descriptive analytic techniques include averages and counts. Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data.

This concept applies complex techniques of classical statistics, like regression and decision trees, to provide credible answers to queries such as: ‘’How exactly will my sales be influenced by a 10% increase in advertising expenditure?’’ This leads to simulations and “what-if” analyses for users to learn more.

All predictive analytics applications involve three fundamental components:

  • Data: The effectiveness of every predictive model strongly depends on the quality of the historical data it processes.
  • Statistical modeling: Includes the various statistical techniques ranging from basic to complex functions used for the derivation of meaning, insight, and inference. Regression is the most commonly used statistical technique.
  • Assumptions: The conclusions drawn from collected and analyzed data usually assume the future will follow a pattern related to the past.

Data analysis is crucial for any business en route to success, and predictive analytics can be applied in numerous ways to enhance business productivity. These include things like marketing campaign optimization, risk assessment, market analysis, and fraud detection.

Business application of predictive analytics: marketing campaign optimization

In the past, valuable marketing campaign resources were wasted by businesses using instincts alone to try to capture market niches. Today, many predictive analytic strategies help businesses identify, engage, and secure suitable markets for their services and products, driving greater efficiency into marketing campaigns.

A clear application is using visitors’ search history and usage patterns on e-commerce websites to make product recommendations. Sites like Amazon increase their chance of sales by recommending products based on specific consumer interests. Predictive analytics now plays a vital role in the marketing operations of real estate, insurance, retail, and almost every other sector.

How machine learning and predictive analytics are related

While businesses must understand the differences between machine learning and predictive analytics, it’s just as important to know how they are related. Basically, machine learning is a predictive analytics branch. Despite having similar aims and processes, there are two main differences between them:

  • Machine learning works out predictions and recalibrates models in real-time automatically after design. Meanwhile, predictive analytics works strictly on “cause” data and must be refreshed with “change” data.
  • Unlike machine learning, predictive analytics still relies on human experts to work out and test the associations between cause and outcome.

Explore machine learning applications and AI software with SAP Leonardo.


Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past. Please feel to connect on: Linkedin: http://linkedin.com/in/shaily Twitter: https://twitter.com/meisshaily