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Intelligent Sales Leads

David Brock

Improving customer experience with intelligent sales leads

I was recently asked to share my views of the impact of Big Data, business intelligence, and data analytics in sales.  We are only beginning to scratch the surface in leveraging Big Data, particularly in sales.  Many other functions have been leveraging big data and rich analytics for years, with great impact.

I’ve been quoted a lot about my view that Big Data and rich analytics are the “pot of gold at the end of the rainbow” for sales and marketing.  These have the greatest potential in driving both sales effectiveness, but also customer experience of anything that I’m seeing.

Judging by the focus on it in blogs and articles, at events like Dreamforce, and others, I’m not alone in that opinion.

Intelligent Sales LeadsThere are many areas in which Big Data and analytics will help improve the customer experience and drive sales and marketing effectiveness.  One area is in providing sales with “Intelligent Leads.”  It’s a far cry from where we are today–at least judging by the prospecting calls I’ve gotten this morning.

Leads–quantity and quality are always an issue, both with marketing and sales.  They are often a bone of contention between the organizations.  Most organizations, frankly are still in the dark ages in lead management and development.  Too many still think a name and number from the phone book, or an email address scraped from the web is a lead.  Too many dollars, euros, yuan, and yen are being wasted on bad leads driven by bad strategy and thinking.

But leading organizations are changing this.  Marketing automation tools have come a long way in helping us engage, nurture, and develop relationships with prospects.  The content management strategies that go along with these tools are critical in informing, educating and developing the customer.  Lead scoring tools have helped us to narrow the gap between what marketing considers a qualified lead and what sales considers a qualified lead.

But there is a richer view of the customer than that currently provided by most of the marketing automation tools.  See most of those tools are about “our” communications and engagement with the customer.  Where we have moved them on their interest/buying path.

Big data and rich analytics enable us to take things to an entirely new level.  They enable us have a richer view of the customer.  They enable us to incorporate data from many sources–internal and external.  They enable us to recognize patterns, events, opportunities.  Leveraging Big data and rich analytics will enable us to create intelligent leads–leads which engage the right prospect at the right time with the right offer.

With intelligent leads, sales people will be engage customers at the peak of interest, when the propensity to buy is highest.  They’ll know exactly what to talk to them about and how to talk to them.  Intelligent leads will turn the customer experience of prospecting from an annoying intrusion to a welcome and timely insight.

Let me take just a simple example.  I spend a huge amount of money on Amazon.  As a result, they have a very rich profile of me, based on my past purchases, every time I sign on, I see recommendations of things I might be interested in.  They are pretty much right on–and I end up buying a lot of their recommendations.  But all their recommendations are based on my history of transactions and searches at Amazon.

Lately, my wife has been “hinting” about our Christmas vacation.  She wants to go to an exotic place.  She’s been researching places like Fiji, Tahiti, and other spots on the web.  She’s started sending me articles and links, and I’ve been researching them.  What if Amazon could see that search history and start recommending travel books on Fiji and Tahiti?  (Believe me, Google sees that history and can generate a great profile, and sell the lead).

Or what if, United Airlines, started seeing that behavior, and sent me an email, “Dave, in recognition for the 10′s of thousands of miles you’ve flown this year, we’ve put together a travel package of flights and hotels to Fiji and Tahiti and are giving you a 15% discount.  Please click here.”

The timeliness and relevance of these messages, tied with a high propensity to buy make these very intelligent leads and enable them to present offers that I have a high likelihood to accept.

This isn’t outlandish thinking, many leaders in B2C sales are either doing or approaching this capability.  The capability exists in B2B sales, as well.  As a simplistic example, I see people from a company hitting on our blogs and websites, I see them searching for us in LinkedIn,  a number of people with sales management, sales operations, and finance are asking for some of our white papers..  I also know from alerts I’ve been receiving, that the company has had market growth challenges.  Their SG&A has been increasing and when you look at the fine print in the financial statements I’m guessing most of the increase is attributable to sales.  A friend of mine, who happens to be a strategic partner of the company, confirms my suspicions and tells me about a lot of organizational changes.

I’m  not as dumb as I look, so I put all these bits and pieces together, thinking,  maybe this company has a sales process problem and I should be prospecting them about how we can help improve their sales process, effectiveness.  and overall go to market strategies.  Guess what, those people want to talk to me!

Organizations are doing this at a much larger, more sophisticated level, with hundreds and thousands of customers, pinpointing opportunities and providing sales people with intelligent leads.

I’ve just presented some very simplistic examples.  The data is there, waiting to be exploited–it exists in lots of places in our companies and outside our companies–but accessible to us.  The tools are there to start identifying patterns and isolating organizations and individuals.

The capability is there to enrich our prospecting, drive better customer experience, and higher conversion rates in leveraging intelligent leads.

Leading organizations are already leveraging this capability in some way and are moving aggressively into exploiting it in richer forms.  We’ve worked with organizations in helping them do this, in one we saw lead conversions go from 17% to in excess of 80%.  Intelligent leads produce results!

Intelligent sales leads provide a rich view of the customer–both enterprises and individuals.  They’re sourced from internal and external data.  They tell you when to talk to a customer, what to talk about, how to talk to them  in a way that is always timely, relevant, insightful, and produces value.

Leveraging intelligent sales leads will change your marketing, change your prospecting, change your customers’ experiences.

Sales and marketing executives need to get together and start thinking about leveraging Big Data and rich analytics.  I think it is the next quantum leap in sales and marketing effectiveness.

Note: This blog post is from one of our featured guest bloggers, David Brock.  The post can also be found on Dave’s blog here.

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Amazing Digital Marketing Trends And Tips To Expand Your Business In 2015

Sunny Popali

Amazing Digital Marketing Trends & Tips To Expand Your Business In 2015The fast-paced world of digital marketing is changing too quickly for most companies to adapt. But staying up to date with the latest industry trends is imperative for anyone involved with expanding a business.

Here are five trends that have shaped the industry this year and that will become more important as we move forward:

  1. Email marketing will need to become smarter

Whether you like it or not, email is the most ubiquitous tool online. Everyone has it, and utilizing it properly can push your marketing ahead of your rivals. Because business use of email is still very widespread, you need to get smarter about email marketing in order to fully realize your business’s marketing strategy. Luckily, there are a number of tools that can help you market more effectively, such as Mailchimp.

  1. Content marketing will become integrated and more valuable

Content is king, and it seems to be getting more important every day. Google and other search engines are focusing more on the content you create as the potential of the online world as marketing tool becomes apparent. Now there seems to be a push for current, relevant content that you can use for your services and promote your business.

Staying fresh with the content you provide is almost as important as ensuring high-quality content. Customers will pay more attention if your content is relevant and timely.

  1. Mobile assets and paid social media are more important than ever

It’s no secret that mobile is key to your marketing efforts. More mobile devices are sold and more people are reading content on mobile screens than ever before, so it is crucial to your overall strategy to have mobile marketing expertise on your team. London-based Abacus Marketing agrees that mobile marketing could overtake desktop website marketing in just a few years.

  1. Big Data for personalization plays a key role

Marketers are increasingly using Big Data to get their brand message out to the public in a more personalized format. One obvious example is Google Trend analysis, a highly useful tool that marketing experts use to obtain the latest on what is trending around the world. You can — and should — use it in your business marketing efforts. Big Data will also let you offer specific content to buyers who are more likely to look for certain items, for example, and offer personalized deals to specific groups of within your customer base. Other tools, which until recently were the stuff of science fiction, are also available that let you do things like use predictive analysis to score leads.

  1. Visual media matters

A picture really is worth a thousand words, as the saying goes, and nobody can deny the effectiveness of a well-designed infographic. In fact, some studies suggest that Millennials are particularly attracted to content with great visuals. Animated gifs and colorful bar graphs have even found their way into heavy-duty financial reports, so why not give them a try in your business marketing efforts?

A few more tips:

  • Always keep your content relevant and current to attract the attention of your target audience.
  • Always keep all your social media and public accounts fresh. Don’t use old content or outdated pictures in any public forum.
  • Your reviews are a proxy for your online reputation, so pay careful attention to them.
  • Much online content is being consumed on mobile now, so focus specifically on the design and usability of your mobile apps.
  • Online marketing is essentially geared towards getting more traffic onto your site. The more people visit, the better your chances of increasing sales.

Want more insight on how digital marketing is evolving? See Shutterstock Report: The Face Of Marketing Is Changing — And It Doesn’t Include Vince Vaughn.

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About Sunny Popali

Sunny Popali is SEO Director at www.tempocreative.com. Tempo Creative is a Phoenix inbound marketing company that has served over 700 clients since 2001. Tempos team specializes in digital and internet marketing services including web design, SEO, social media and strategy.

Social Media Matters: 6 Content And Social Media Trend Predictions For 2016 [INFOGRAPHIC]

Julie Ellis

As 2015 winds down, it’s time to look forward to 2016 and explore the social media and content marketing trends that will impact marketing strategies over the next 15 months or so.

Some of the upcoming trends simply indicate an intensification of current trends, however others indicate that there are new things that will have a big impact in 2016.

Take a look at a few trends that should definitely factor in your planning for 2016.

1. SEO will focus more on social media platforms and less on search engines

Clearly Google is going nowhere. In fact, in 2016 Google’s word will still essentially be law when it comes to search engine optimization.

However, in 2016 there will be some changes in SEO. Many of these changes will be due to the fact that users are increasingly searching for products and services directly from websites such as Facebook, Pinterest, and YouTube.

There are two reasons for this shift in customer habits:

  • Customers are relying more and more on customer comments, feedback, and reviews before making purchasing decisions. This means that they are most likely to search directly on platforms where they can find that information.
  • Customers who are seeking information about products and services feel that video- and image-based content is more trustworthy.

2. The need to optimize for mobile and touchscreens will intensify

Consumers are using their mobile devices and tablets for the following tasks at a sharply increasing rate:

  • Sending and receiving emails and messages
  • Making purchases
  • Researching products and services
  • Watching videos
  • Reading or writing reviews and comments
  • Obtaining driving directions and using navigation apps
  • Visiting news and entertainment websites
  • Using social media

Most marketers would be hard-pressed to look at this list and see any case for continuing to avoid mobile and touchscreen optimization. Yet, for some reason many companies still see mobile optimization as something that is nice to do, but not urgent.

This lack of a sense of urgency seemingly ignores the fact that more than 80% of the highest growing group of consumers indicate that it is highly important that retailers provide mobile apps that work well. According to the same study, nearly 90% of Millennials believe that there are a large number of websites that have not done a very good job of optimizing for mobile.

3. Content marketing will move to edgier social media platforms

Platforms such as Instagram and Snapchat weren’t considered to be valid targets for mainstream content marketing efforts until now.

This is because they were considered to be too unproven and too “on the fringe” to warrant the time and marketing budget investments, when platforms such as Facebook and YouTube were so popular and had proven track records when it came to content marketing opportunity and success.

However, now that Instagram is enjoying such tremendous growth, and is opening up advertising opportunities to businesses beyond its brand partners, it (along with other platforms) will be seen as more and more viable in 2016.

4. Facebook will remain a strong player, but the demographic of the average user will age

In 2016, Facebook will likely remain the flagship social media website when it comes to sharing and promoting content, engaging with customers, and increasing Internet recognition.

However, it will become less and less possible to ignore the fact that younger consumers are moving away from the platform as their primary source of online social interaction and content consumption. Some companies may be able to maintain status quo for 2016 without feeling any negative impacts.

However, others may need to rethink their content marketing strategies for 2016 to take these shifts into account. Depending on their branding and the products or services that they offer, some companies may be able to profit from these changes by customizing the content that they promote on Facebook for an older demographic.

5. Content production must reflect quality and variety

  • Both B2B and B2C buyers value video based content over text based content.
  • While some curated content is a good thing, consumers believe that custom content is an indication that a company wishes to create a relationship with them.
  • The great majority of these same consumers report that customized content is useful for them.
  • B2B customers prefer learning about products and services through content as opposed to paid advertising.
  • Consumers believe that videos are more trustworthy forms of content than text.

Here is a great infographic depicting the importance of video in content marketing efforts:
Small Business Video infographic

A final, very important thing to note when considering content trends for 2016 is the decreasing value of the keyword as a way of optimizing content. In fact, in an effort to crack down on keyword stuffing, Google’s optimization rules have been updated to to kick offending sites out of prime SERP positions.

6. Oculus Rift will create significant changes in customer engagement

Oculus Rift is not likely to offer much to marketers in 2016. After all, it isn’t expected to ship to consumers until the first quarter. However, what Oculus Rift will do is influence the decisions that marketers make when it comes to creating customer interaction.

For example, companies that have not yet embraced storytelling may want to make 2016 the year that they do just that, because later in 2016 Oculus Rift may be the platform that their competitors will be using to tell stories while giving consumers a 360-degree vantage point.

For a deeper dive on engaging with customers through storytelling, see Brand Storytelling: Where Humanity Takes Center Stage.

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About Julie Ellis

Julie Ellis – marketer and professional blogger, writes about social media, education, self-improvement, marketing and psychology. To contact Julie follow her on Twitter or LinkedIn.

Unlock Your Digital Super Powers: How Digitization Helps Companies Be Live Businesses

Erik Marcade and Fawn Fitter

The Port of Hamburg handles 9 million cargo containers a year, making it one of the world’s busiest container ports. According to the Hamburg Port Authority (HPA), that volume doubled in the last decade, and it’s expected to at least double again in the next decade—but there’s no room to build new roads in the center of Hamburg, one of Germany’s historic cities. The port needed a way to move more freight more efficiently with the physical infrastructure it already has.

sap_Q216_digital_double_feature1_images1The answer, according to an article on ZDNet, was to digitize the processes of managing traffic into, within, and back out of the port. By deploying a combination of sensors, telematics systems, smart algorithms, and cloud data processing, the Port of Hamburg now collects and analyzes a vast amount of data about ship arrivals and delays, parking availability, ground traffic, active roadwork, and more. It generates a continuously updated model of current port conditions, then pushes the results through mobile apps to truck drivers, letting them know exactly when ships are ready to drop off or receive containers and optimizing their routes. According to the HPA, they are now on track to handle 25 million cargo containers a year by 2025 without further congestion or construction, helping shipping companies bring more goods and raw materials in less time to businesses and consumers all across Europe.

In the past, the port could only have solved its problem with backhoes and building permits—which, given the physical constraints, means the problem would have been unsolvable. Today, though, software and sensors are allowing it to improve processes and operations to a previously impossible extent. Big Data analysis, data mining, machine learning, artificial intelligence (AI), and other technologies have finally become sophisticated enough to identify patterns not just in terabytes but in petabytes of data, make decisions accordingly, and learn from the results, all in seconds. These technologies make it possible to digitize all kinds of business processes, helping organizations become more responsive to changing market conditions and more able to customize interactions to individual customer needs. Digitization also streamlines and automates these processes, freeing employees to focus on tasks that require a human touch, like developing innovative strategies or navigating office politics.

In short, digitizing business processes is key to ensuring that the business can deliver relevant, personalized responses to the market in real time. And that, in turn, is the foundation of the Live Business—a business able to coordinate multiple functions in order to respond to and even anticipate customer demand at any moment.

Some industries and organizations are on the verge of discovering how business process digitization can help them go live. Others have already started putting it into action: fine-tuning operations to an unprecedented level across departments and at every point in the supply chain, cutting costs while turbocharging productivity, and spotting trends and making decisions at speeds that can only be called superhuman.

Balancing Insight and Action

sap_Q216_digital_double_feature1_images2Two kinds of algorithms drive process digitization, says Chandran Saravana, senior director of advanced analytics at SAP. Edge algorithms operate at the point where customers or other end users interact directly with a sensor, application, or Internet-enabled device. These algorithms, such as speech or image recognition, focus on simplicity and accuracy. They make decisions based primarily on their ability to interpret input with precision and then deliver a result in real time.

Edge algorithms work in tandem with, and sometimes mature into, server-level algorithms, which report on both the results of data analysis and the analytical process itself. For example, the complex systems that generate credit scores assess how creditworthy an individual is, but they also explain to both the lender and the credit applicant why a score is low or high, what factors went into calculating it, and what an applicant can do to raise the score in the future. These server-based algorithms gather data from edge algorithms, learn from their own results, and become more accurate through continuous feedback. The business can then track the results over time to understand how well the digitized process is performing and how to improve it.

sap_Q216_digital_double_feature1_images5From Data Scarcity to a Glut

To operate in real time, businesses need an accurate data model that compares what’s already known about a situation to what’s happened in similar situations in the past to reach a lightning-fast conclusion about what’s most likely to happen next. The greatest barrier to this level of responsiveness used to be a lack of data, but the exponential growth of data volumes in the last decade has flipped this problem on its head. Today, the big challenge for companies is having too much data and not enough time or power to process it, says Saravana.

Even the smartest human is incapable of gathering all the data about a given situation, never mind considering all the possible outcomes. Nor can a human mind reach conclusions at the speed necessary to drive Live Business. On the other hand, carefully crafted algorithms can process terabytes or even petabytes of data, analyze patterns and detect outliers, arrive at a decision in seconds or less—and even learn from their mistakes (see How to Train Your Algorithm).

How to Train Your Algorithm 

The data that feeds process digitization can’t just simmer.
It needs constant stirring.

Successfully digitizing a business process requires you to build a model of the business process based on existing data. For example, a bank creates a customer record that includes not just the customer’s name, address, and date of birth but also the amount and date of the first deposit, the type of account, and so forth. Over time, as the customer develops a history with the bank and the bank introduces new products and services, customer records expand to include more data. Predictive analytics can then extrapolate from these records to reach conclusions about new customers, such as calculating the likelihood that someone who just opened a money market account with a large balance will apply for a mortgage in the next year.

Germany --- Germany, Lower Bavaria, Man training English Springer Spaniel in grass field --- Image by © Roman M‰rzinger/Westend61/CorbisTo keep data models accurate, you have to have enough data to ensure that your models are complete—that is, that they account for every possible predictable outcome. The model also has to push outlying data and exceptions, which create unpredictable outcomes, to human beings who can address their special circumstances. For example, an algorithm may be able to determine that a delivery will fail to show up as scheduled and can point to the most likely reasons why, but it can only do that based on the data it can access. It may take a human to start the process of locating the misdirected shipment, expediting a replacement, and establishing what went wrong by using business knowledge not yet included in the data model.

Indeed, data models need to be monitored for relevance. Whenever the results of a predictive model start to drift significantly from expectations, it’s time to examine the model to determine whether you need to dump old data that no longer reflects your customer base, add a new product or subtract a defunct one, or include a new variable, such as marital status or length of customer relationship that further refines your results.

It’s also important to remember that data doesn’t need to be perfect—and, in fact, probably shouldn’t be, no matter what you might have heard about the difficulty of starting predictive analytics with lower-quality data. To train an optical character recognition system to recognize and read handwriting in real time, for example, your samples of block printing and cursive writing data stores also have to include a few sloppy scrawls so the system can learn to decode them.

On the other hand, in a fast-changing marketplace, all the products and services in your database need consistent and unchanging references, even though outside the database, names, SKUs, and other identifiers for a single item may vary from one month or one order to the next. Without consistency, your business process model won’t be accurate, nor will the results.

Finally, when you’re using algorithms to generate recommendations to drive your business process, the process needs to include opportunities to test new messages and products against existing successful ones as well as against random offerings, Saravana says. Otherwise, instead of responding to your customers’ needs, your automated system will actually control their choices by presenting them with only a limited group of options drawn from those that have already received the most
positive results.

Any process is only as good as it’s been designed to be. Digitizing business processes doesn’t eliminate the possibility of mistakes and problems; but it does ensure that the mistakes and problems that arise are easy to spot and fix.

From Waste to Gold

Organizations moving to digitize and streamline core processes are even discovering new business opportunities and building new digitized models around them. That’s what happened at Hopper, an airfare prediction app firm in Cambridge, Massachusetts, which discovered in 2013 that it could mine its archives of billions of itineraries to spot historical trends in airfare pricing—data that was previously considered “waste product,” according to Hopper’s chief data scientist, Patrick Surry.

Hopper developed AI algorithms to correlate those past trends with current fares and to predict whether and when the price of any given flight was likely to rise or fall. The results were so accurate that Hopper jettisoned its previous business model. “We check up to 3 billion itineraries live, in real time, each day, then compare them to the last three to four years of historical airfare data,” Surry says. “When consumers ask our smartphone app whether they should buy now or wait, we can tell them, ‘yes, that’s a good deal, buy it now,’ or ‘no, we think that fare is too expensive, we predict it will drop, and we’ll alert you when it does.’ And we can give them that answer in less than one second.”

When consumers ask our smartphone app whether they should buy now or wait, we can tell them, ‘yes, that’s a good deal, buy it now’.

— Patrick Surry, chief data scientist, Hopper

While trying to predict airfare trends is nothing new, Hopper has told TechCrunch that it can not only save users up to 40% on airfares but it can also find them the lowest possible price 95% of the time. Surry says that’s all due to Hopper’s algorithms and data models.

The Hopper app launched on iOS in January 2015 and on Android eight months later. The company also switched in September 2015 from directing customers to external travel agencies to taking bookings directly through the app for a small fee. The Hopper app has already been downloaded to more than 2 million phones worldwide.

Surry predicts that we’ll soon see sophisticated chatbots that can start with vague requests from customers like “I want to go somewhere warm in February for less than $500,” proceed to ask questions that help users narrow their options, and finally book a trip that meets all their desired parameters. Eventually, he says, these chatbots will be able to handle millions of interactions simultaneously, allowing a wide variety of companies to reassign human call center agents to the handling of high-value transactions and exceptions to the rules built into the digitized booking process.

Port of Hamburg Lets the Machines Untangle Complexity

In early 2015, AI experts told Wired magazine that at least another 10 years would pass before a computer could best the top human players at Go, an ancient game that’s exponentially harder than chess. Yet before the end of that same year, Wired also reported that machine learning techniques drove Google’s AlphaGo AI to win four games out of five against one of the world’s top Go players. This feat proves just how good algorithms have become at managing extremely complex situations with multiple interdependent choices, Saravana points out.

The Port of Hamburg, which has digitized traffic management for an estimated 40,000 trucks a day, is a good example. In the past, truck drivers had to show up at the port to check traffic and parking message boards. If they arrived before their ships docked, they had to drive around or park in the neighboring residential area, contributing to congestion and air pollution while they waited to load or unload. Today, the HPA’s smartPORT mobile app tracks individual trucks using telematics. It customizes the information that drivers receive based on location and optimizes truck routes and parking in real time so drivers can make more stops a day with less wasted time and fuel.

The platform that drives the smartPORT app also uses sensor data in other ways: it tracks wind speed and direction and transmits the data to ship pilots so they can navigate in and out of the port more safely. It monitors emissions and their impact on air quality in various locations in order to adjust operations in real time for better control over environmental impact. It automatically activates streetlights for vehicle and pedestrian traffic, then switches them off again to save energy when the road is empty. This ability to coordinate and optimize multiple business functions on the fly makes the Port of Hamburg a textbook example of a Live Business.

Digitization Is Not Bounded by Industry

Other retail and B2B businesses of all types will inevitably join the Port of Hamburg in further digitizing processes, both in predictable ways and in those we can only begin to imagine.

sap_Q216_digital_double_feature1_images4Customer service, for example, is likely to be in the vanguard. Automated systems already feed information about customers to online and phone-based service representatives in real time, generate cross-selling and upselling opportunities based on past transactions, and answer customers’ frequently asked questions. Saravana foresees these systems becoming even more sophisticated, powered by AI algorithms that are virtually indistinguishable from human customer service agents in their ability to handle complex live interactions in real time.

In manufacturing and IT, Sven Bauszus, global vice president and general manager for predictive analytics at SAP, forecasts that sensors and predictive analysis will further automate the process of scheduling and performing maintenance, such as monitoring equipment for signs of failure in real time, predicting when parts or entire machines will need replacement, and even ordering replacements preemptively. Similarly, combining AI, sensors, data mining, and other technologies will enable factories to optimize workforce assignments in real time based on past trends, current orders, and changing market conditions.

Public health will be able to go live with technology that spots outbreaks of infectious disease, determines where medical professionals and support personnel are needed most and how many to send, and helps ensure that they arrive quickly with the right medication and equipment to treat patients and eradicate the root cause. It will also make it easier to track communicable illnesses, find people who are symptomatic, and recommend approaches to controlling the spread of the illness, Bauszus says.

He also predicts that the insurance industry, which has already begun to digitize its claims-handling processes, will refine its ability to sort through more claims in less time with greater accuracy and higher customer satisfaction. Algorithms will be better and faster at flagging claims that have a high probability of being fraudulent and then pushing them to claims inspectors for investigation. Simultaneously, the same technology will be able to identify and resolve valid claims in real time, possibly even cutting a check or depositing money directly into the insured person’s bank account within minutes.

Financial services firms will be able to apply machine learning, data mining, and AI to accelerate the process of rating borrowers’ credit and detecting fraud. Instead of filling out a detailed application, consumers might be able to get on-the-spot approval for a credit card or loan after inputting only enough information to be identified. Similarly, banks will be able to alert customers to suspicious transactions by text message or phone call—not within a day or an hour, as is common now, but in a minute or less.

Pitfalls and Possibilities

As intelligent as business processes can be programmed to be, there will always be a point beyond which they have to be supervised. Indeed, Saravana forecasts increasing regulation around when business processes can and can’t be digitized. Especially in areas involving data security, physical security, and health and safety, it’s one thing to allow machines to parse data and arrive at decisions to drive a critical business process, but it’s another thing entirely to allow them to act on those decisions without human oversight.

Automated, impersonal decision making is fine for supply chain automation, demand forecasting, inventory management, and other processes that need faster-than-human response times. In human-facing interactions, though, Saravana insists that it’s still best to digitize the part of the process that generates decisions, but leave it to a human to finalize the decision and decide how to put it into action.

“Any time the interaction is machine-to-machine, you don’t need a human to slow the process down,” he says. “But when the interaction involves a person, it’s much more tricky, because people have preferences, tastes, the ability to try something different, the ability to get fatigued—people are only statistically predictable.”

For example, technology has made it entirely possible to build a corporate security system that can gather information from cameras, sensors, voice recognition technology, and other IP-enabled devices. The system can then feed that information in a steady stream to an algorithm designed to identify potentially suspicious activity and act in real time to prevent or stop it while alerting the authorities. But what happens when an executive stays in the office unusually late to work on a presentation and the security system misidentifies her as an unauthorized intruder? What if the algorithm decides to lock the emergency exits, shut down the executive’s network access, or disable her with a Taser instead of simply sending an alert to the head of security asking what to do while waiting for the police to come?

sap_Q216_digital_double_feature1_images6The Risk Is Doing Nothing

The greater, if less dramatic, risk associated with digitizing business processes is simply failing to pursue it. It’s true that taking advantage of new digital technologies can be costly in the short term. There’s no question that companies have to invest in hardware, software, and qualified staff in order to prepare enormous data volumes for storage and analysis. They also have to implement new data sources such as sensors or Internet-connected devices, develop data models, and create and test algorithms to drive business processes that are currently analog. But as with any new technology, Saravana advises, it’s better to start small with a key use case, rack up a quick win with high ROI, and expand gradually than to drag your heels out of a failure to grasp the long-term potential.

The economy is digitizing rapidly, but not evenly. According to the McKinsey Global Institute’s December 2015 Digital America report, “The race to keep up with technology and put it to the most effective business use is producing digital ‘haves’ and ‘have-mores’—and the large, persistent gap between them is becoming a decisive factor in competition across the economy.” Companies that want to be among the have-mores need to commit to Live Business today. Failing to explore it now will put them on the wrong side of the gap and, in the long run, rack up a high price tag in unrealized efficiencies and missed opportunities. D!

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Erik Marcade

About Erik Marcade

Erik Marcade is vice president of Advanced Analytics Products at SAP.

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How The World Of Work Is Changing [INFOGRAPHIC]

Lauren Kirkpatrick

The workplace is dramatically different than it was a few years ago. Technology advancements and social media have changed the landscape and are still changing it. Social change has also made an impact on the workforce with more women taking roles in what used to be a “man’s world.”

As we continue to move through advancements, legislative changes, social changes, and different initiatives, what will the world of work look like for future generations? Thanks to our friends at NeoNam Studios, check out this awesome infographic that breaks down what we might be looking at in the future.

world of work changing

How the World of Work is Changing [Infographic] by Next Generation

For more insight on the changing workplace, see Why Social Media Is Shaping The Future Of Work.

 

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