How Prescriptive Recruiting Improves The Odds Of Finding Your Best Match

Jeff Mills

Most people like to equate the recruiting process with dating. Starting with a gentle introduction from a mutual acquaintance or with a simple greeting, the relationship steadily escalates over coffee, phone calls, text messages, emails, and perhaps an interview or three. Then the inevitable happens: days, if not weeks, can go by until the recruiter calls back again.

Approximately 60% of us have been there, according to the Future Workplace & CareerArc study, conducted by Workplace Trends. We sit at home wondering where it all went wrong and what we could have done better. But really, it’s the recruiting process that went wrong, not how we presented ourselves.

In today’s 24×7 digital world, time is of the essence when it comes to acquiring new talent. In fact, TalentBoard’s North American Candidate Experience Research Report revealed that 49% of surveyed job candidates experience a lapse of one week between the last interview and the offer letter. Unfortunately for recruiters bogged down with the complexity of working with multiple teams and a dizzying array of channels and solutions, this moment of silence can turn into a moment of lost top talent.

The importance of time-tested best practices for hiring the best talent

Very rare is the person who can wait days – or even weeks – in dead silence to find out whether they are being offered a job without any type of expectation setting. Sometimes there’s another company, most likely a competitor, waiting in the wings to hire them before someone else does. Other times, the candidate’s employer may consider options to convince them not to leave.

Recently, I was reminded of how much an excellent recruiting process can make a difference. I was engaged in the interviewing process for two separate companies at the same time. I spent more than a week talking and meeting executives at both companies. When everything was said and done, I received a phone call that an offer would be coming soon. A few days later, I received the offer. But I didn’t immediately accept it because I wanted to know what the other company would propose. For a few days, I waited for that second offer letter – and grew more impatient. After a week of following up but not hearing anything, I seriously questioned that company’s interest.

Although I can safely say that I accepted the original offer for a multitude of reasons, the mutual respect between my hiring manager, myself, and the recruiter was a critical factor in my decision. I did receive the second offer a day after I accepted my original offer. The second company was not happy I had selected another offer, but seriously what do they expect given their poor communication and lack of respect for someone’s time and effort.

This situation happens to companies and candidates every day, but it doesn’t have to be this way. With the right tools, a company’s employer brand can maintain a highly visible and attractive experience that keeps candidates engaged, vested, and immune to competing overtures and promises. This may be a tall order for the HR organization to achieve, but it’s possible with the use of industry-leading practices, or what we call a “model company.”

Why your recruiters need to act like a model company

First off, I am a firm believer that organizational transformation is 90% process and 10% product. As a set of highly researched, rapidly configured end-to-end reference solutions, model company services quickly address the specific demands of the recruiting experience. The latest applications and validated best practices help evolve every aspect of the process – from the perspective of the recruiter and of the job candidate. Plus, the approach helps remove administrative complexities, future-proof new technology adoption, leverage new business rules, shorten the time to fill a position, and reduce the cost per hire.

Value-adding, strategic, and up-to-date model company services deliver unprecedented capabilities to four primary areas of the recruiting process:

  • Requisition: Best practices and prescribed business rules help shorten time to hire from weeks to just a day or two. Over time, this benefit can compound into thousands of recruiting hours saved, which is a massive enhancement to productivity. With a streamlined requisition process, recruiters can create a job request and start distributing across channels quickly in the most appropriate formats. Plus recruiters can engage in more meaningful work and focus more on the candidate relationship by removing tasks that provide little value to the final outcome and are not required by regulations.
  • Candidate experience: When people apply for a job, they want a fast, easy way to know which positions are open, why employees like working for the employer, how to submit their application, and whether the application is being reviewed. Addressing each of these areas with predefined templates and processes can help recruiters gain a significant advantage over their competitors that do not provide a leading candidate experience. By minimizing the complexity of managing job content and applying appropriate prescreening practices, the application drop-off rate decreases while overall candidate satisfaction increases.
  • Candidate selection: For any given requisition, recruiters can spend hours upon hours reviewing applications. Proven efficiencies in screening and assessments can help narrow the field, followed by streamlined, data-oriented interview processes and efficient offer approvals. One of the most promising, yet untapped, areas in candidate selection is the ability to generate a list of recommended candidates through machine learning and predictive analytics. These best practices can help ensure that the hiring manager is included throughout the process – not just during the interview – to play a more significant role in being a partner to recruiting and ensuring candidate success.
  • Offer-to-onboarding process: After significant time, mindshare, and money are spent on acquiring the right person for the job, a seamless transition from “candidate” to “new hire” is essential. All too often, a lack of engagement and alignment between the hiring manager and the new hire leads to short-term attrition. When seamlessly integrated with the recruiting process, onboarding can turn the candidate experience into employee engagement by allowing hiring managers to interact with their team members without disruption.

It’s time to run the recruiting process more like a courtship

Ultimately, companies that don’t show interest in their candidates are the ones that will lose out on the best talent available. For recruiters, hiring managers, and candidates, model company services can quickly change the success of talent acquisition by streamlining each step of the process to accelerate time to hire and provide full transparency to all parties. With this approach, recruiters will do more than source, select, and build relationships with their candidates – they will also serve as the first line of action for employee engagement.

To learn more about SAP Model Company for HR, check out the white paper “Turning People Strategies into a Catalyst for Change: A Prescriptive, Preconfigured, and Leading-Practice Approach to HR Digitalization.”


Jeff Mills

About Jeff Mills

Jeff Mills is Director of Solution Management for Talent Acquisition at SAP SuccessFactors. He has a long history in SaaS, product marketing, digital marketing, and user behavior. Before joining SuccessFactors, Jeff has held marketing leadership roles in customer profile management and governance, risk, and compliance as well as led the product division in email marketing and ecommerce and was a researcher at Gartner.

How Technology And Data-Driven Insight Can Boost Employee Engagement

Andre Smith

Human resources professionals know that happier employees are more productive. In today’s hyper-competitive global economy, employee productivity can mean the difference between business success and failure. That means employee happiness should be a top priority for any company that aims to succeed.

The difference between a happy, engaged workforce and a dissatisfied one is vast. Surveys indicate that companies with highly engaged employees outperform others by as much as 202%. Still, according to Gallup polling data, only about 32% of employees report that they feel motivated and engaged at work. To fix the problem, we must first understand what causes it. Here are the most common roadblocks to employee engagement, and how technology and data-driven management can help overcome them.

Rigid schedules

In a recent survey, as many as 70% of employees reported that having flexible work hours was very important to them. In today’s modern interconnected world, it’s easier than ever to create flexible work arrangements for employees. The key to making it work is to utilize comprehensive workforce management software to analyze business needs before beginning a flexible work initiative.

Gary Corcoran, of Advance Systems, says, “Gaining a full picture of necessary staffing levels throughout the workweek is the first step to creating a flexible schedule. In reality, the flexibility allowed should extend as far as business needs will allow. That way, employees stay happy and the business won’t find itself short-staffed at busy times.”

Lack of work/life balance

In 2016, American workers failed to use a combined 662 million earned vacation days. A big reason for this is anxiety about requesting vacation time. The results are profoundly damaging for both employees and companies. Once again, a data-driven solution is in order. By keeping careful track of which employees aren’t taking vacation time, human resource managers can intervene to make sure they take a break.

This goes a long way towards changing the office culture surrounding vacations. Depending on the business structure, making vacations mandatory can create a positive change. Companies can even offer automated paycheck deductions into vacation savings accounts using services like 401Play to encourage health employee vacation habits.

Poor internal communication

One of the most common employee complaints is lack of transparency and communication within their organization. Not seeing clear reasons for their work or understanding their place within the bigger picture is dispiriting and counterproductive. To combat this, a variety of technological tools may be employed. First and foremost, the internal communication system should include an all-in-one platform like Slack, which all employees can use to remain connected with one another. At the team level, project-based communication tools like i done this make task management a snap and help employees to see how their work dovetails with that of their co-workers.

Engagement begins at the top

There are many other factors that can contribute to employee engagement than mentioned here. There is, however, an easy, but often overlooked, way for managers to boost employee engagement: They must embody their own engagement policies. For instance, if the business allows flexible scheduling, managers should use it as well, always striving to stay productive and set an example.

The same concept goes for things like vacation time and communications: It’s all about setting a tone. The level of commitment to creating a healthy and motivated workplace at the management level is the true determining factor in the success of any engagement policy. Efforts by managers let employees know that they are valued. That creates the kind of engagement that cannot be bought or quantified.

Learn more about how data analytics in HR can get your business Moving From Gut Instinct to Data Insight.


Andre Smith

About Andre Smith

Andre Smith is an Internet, marketing, and e-commerce specialist with several years of experience in the industry. He has watched as the world of online business has grown and adapted to new technologies, and he has made it his mission to help keep businesses informed and up to date.

Are Your Performance Reviews Ahead Of The Curve Or Just A Box-Ticking Affair?

Sonya Clark

How many times have you sat through your performance review and felt like it was a box-ticking exercise? This approach to performance management may have worked 20 or even five years ago, but workplaces have changed.

Globally, only 13% of employees are engaged in their jobs. In fact, actively disengaged workers worldwide continue to outnumber engaged workers at a rate of nearly 2 to 1.

In Germany alone, Gallup estimates that disengagement costs €112 billion to €138 billion per year. Companies with engaged employees outperform those without by up to 202%. The need to dramatically change the way we manage employee engagement and performance couldn’t be more urgent. Truth is, what we’ve known as performance management is not working.

Companies of all sizes are shifting away from annual appraisals to more regular check-ins and frequent real-time feedback. According to Deloitte, “70% of executives are finding that the redesign of performance management is now a high priority.”

Now that we are well into 2018, companies will follow the example of global giants such as SAP and Nestle, which have stripped complexity, such as annual appraisals, ratings, calibration meetings, and competency assessments, focusing instead on regular, quality performance conversations and feedback known as Continuous Performance Management (CPM).

SAP’s head of HR for Australia and New Zealand, Debbie Rigger, believes that CPM comes down to systems, process, and people. Questions she recently explored with Queensland HR leaders include: How do you set the bar at the right level? How do you monitor and assess performance? And how do you do all of this is a simple and transparent way?

CPM: A new approach

At SAP, we needed an updated approach to performance. In order to be agile and keep up with our customers, we needed to head in a different direction, so by early 2017 we rolled out CPM, which resulted in huge gains:

  • 88% of employees are having continuous dialogue
  • 79% are living the new continuous dialogue culture
  • There’s been an 80% increase in engagement in development planning

Let’s face it, everyone wants to know how they are doing at work. By way of comparison, if you play sports, feedback is instant when you are on the field – as a result, development and improvement are much faster. Your coach is there to give you direction, offer support, and help you through the challenges. Ultimately a good coach will also be there to celebrate the wins, and help you to be the best you can be – every step of the way… Not just once a year. Why should the workplace be any different?

Technology provides an auditable trail that facilitates a more rounded conversation about the highs and lows of the past 12 months. It also takes away the reliance (and risk!) of memorizing events – which can be skewed in hindsight. Ultimately, technology creates a level playing field for everybody. It bridges the gap between departments, distance, and generations.

To get more HR-related insights, including SAP SuccessFactors customer stories, please visit our HR Insights Digital Hub.


Sonya Clark

About Sonya Clark

Sonya Clark is a HR Specialist with SAP SuccessFactors. For close to 15 years, she has partnered with HR and Business leaders to align their people strategies to their business strategies, delivering people initiatives that increase employee engagement and productivity. Using a combination of both best practise, and leading edge technologies offering her clients a design approach to intelligent HR management to ensure a return on investment. Based in Brisbane, she is regularly hosting HR thought leadership events, whilst partnering with HR experts to deliver strategic solution advice.

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: Twitter: