Finding Value In IoT Data


One day soon, we will wake up and wonder how we ever survived in a world of “dumb” disconnected things. Our homes, including our pantries, closets, and shoe racks, and our offices, factories, and vehicles will be full of connected devices.

The World Economic Forum estimates that the number of connected devices will grow at a compound annual growth rate (CAGR) of 21.6% over the next four years from 22.9 billion in 2016 to a headline-grabbing 50.1 billion by 2020 – equivalent to almost five connected devices for every person on the planet.

By 2020, there will be an estimated 5 connected devices to every 1 person on the planet.

But that will be just the beginning. Welcome to the Internet of Things (IoT).

Underpinning the growth of IoT are tumbling prices for the sensors that turn “dumb” things into “smart” devices and capture data from the environment around them, and the vast data-centric and mostly wireless networks that connect these devices to each other and to the broader Internet.

As the sensors grow ever cheaper, and the network grows ever larger, the more data we as individuals, professionals, companies, and governments can collect and analyze to make ever more intelligent decisions.

Just like other commoditizing electronic components, fierce competition, and Moore’s Law has driven down prices, especially for accelerometers and gyroscope sensors typically used in smartphones and other mobile devices.

As a result, manufacturers can add sensor and communications modules to almost any product for a few dollars, bringing the day when everything (valued at $10 or more is) I0T-ready a big step closer.

“Our perspective is that cost of both the sensors and devices is approaching free and the size is approaching invisible,” said James Bailey, managing director of the mobility practice at Accenture, last year. “Literally everything will have IoT technology at some point.”

At the same time, the cost of embedded processors, networking and cloud-based computing – other key components in the IoT world – have all fallen.

The opportunity for transformation

IoT, particularly the Internet of Industrial Internet of Things (IoIT), is about hyperconnectivity and sensor-generated data – huge amounts of it. But the real value lies in what you can do with that data – in the outcomes it enables, rather than the collection, transmission, or storage of that data.

“We need more data-driven decision making,” said Tanja Rückert, executive vice president of Digital Assets and IoT at SAP,  during the SAP Executive Summit on the Internet of Things that took place earlier this month.

Her views were echoed by Nils Herzberg, senior vice president and global co-lead of IoT Go to Market, who stressed that “data is the fuel of the 21st century.”

Nevertheless, a recent study found that while 81 percent of business executives believe that successful adoption of industrial IoT is critical to their company’s future success, only 25 percent have a clear industrial IoT strategy.

A challenge and a huge opportunity remains for those enterprise software and services companies that have the technology and tools available to help people and businesses make sense of, analyze, and harness the tsunami of data that we are about to be engulfed by.

Here’s the real business potential to add value through IoT: Companies in almost every industry will transform into digital businesses which means oversight must be powered by real-time data – fed in large part by sensors.

As Herzberg, says, the beauty of sensors that they bring real-time data to applications: “Customers run applications for business critical processes, which could run better with real-time awareness.”

Big Data analytics and machine learning will deliver personal and business insights and will enable us to make immediate decisions based on that data – rather than relying as we have in the past, on guesswork or out-of-date forecasts. “When sensors provide real-time information, customers can make better decisions, rather than using guess work,” says Herzberg.

IoT data is already helping companies track goods on their way through the supply chain and immediately alert managers in case of theft or damage, reducing waiting times in busy ports, playing a key roll in jet engine and tractor predictive maintenance, helping farmers optimize crop yields, and improving safety across a number of public and private enterprises.

The market

So how big is the market opportunity? Cisco, the networking equipment group, predicts the global Internet of Things market will be $14.4 trillion by 2022, with the majority invested in improving customer experiences.

Cisco suggested that additional areas of investment would include reducing the time-to-market ($3T), improving supply chain and logistics ($2.7T) and cost reduction strategies ($2.5T) and increasing employee productivity ($2.5T).

But the implications of IoT and the Big Data analytics that it feeds will go far beyond traditional business models and have a profound impact on both enterprises and individuals. When combined with machine learning and cognitive computing, the insights derived from IoT data will enable us as individuals and businesses users to deploy intelligent agents empowered to make autonomous decisions and negotiate with other agents on our behalf.

This is not about machines replacing humans. Rather, intelligent apps augment humans’ ability to run the business. Predicted businesses will deploy intelligent agents across multiple areas to help all employees, from sales to suppliers to shop floor.

Things to outcomes

Ultimately, machines will help people understand connections between information by monitoring, analyzing, and correlating data that people wouldn’t see ordinarily. This helps people improve outcomes. For example, in healthcare it can mean improving patients’ recovery times.

Enterprise IoT may be Big Data’s killer app, but ultimately it is still about people.


Do Companies Get a Digital Home Field Advantage?

sap_Q316_digital_double_charted_inforgraphicThe digital technologies that are transforming the world economy have converted once-solid industry boundaries into permeable membranes through which new players may enter—or exit. But for established firms, the smartest move right now may be to reinvent their existing markets rather than pursue ventures in unfamiliar business segments.We used S&P Global Market Intelligence’s Compustat database to examine the diversification behavior of 1,932 companies in 10 industries between 2007—the year the Android operating system and the iPhone debuted—and 2015. Only a handful of firms reported entering a new market segment or exiting an existing one. Analyzing the overall returns showed companies entering new business segments (as defined by the North American Industry Classification System) increased their revenue by an average US$437 million.

However, the companies that charged into new segments were less profitable on average, as measured by return on assets, compared to companies that made no changes or that consolidated into fewer segments (the consolidating firms were the most profitable).

Given that diversification requires investment, it’s possible that companies making strategic moves into new segments have not yet realized the payoff from doing so. Nevertheless, the findings align with the conclusions of a 2015 Economist Intelligence Unit survey (sponsored by SAP) in which more than half (57%) of executives said digital disruption by established competitors posed a greater threat than new industry entrants.


In the Digital Era, Disruption Comes from Within

Companies that stay focused on core business segments are most profitable



Comparison of average rates of change in company-level returns on assets, 2007—2015

Find the New Business Models Within

sap_Q316_digital_double_charted_images1Digital technologies are now fundamental to creating new business opportunities, observes Pontus Siren, a partner at innovation consulting firm Innosight. Companies are finding profitable ideas close to home by using new technologies to transform processes or capitalizing on data they capture from their existing businesses. For example, Disney’s MagicBand, the chip-enabled bracelet that patrons use to buy passes, food, and souvenirs, “is a great example [of] where they are not fundamentally changing the business, but they are transforming the experience,” Siren says.

Using digital technologies to become more efficient or to create a better customer experience should ultimately lead to higher revenue and profits. But companies pursuing digital transformation need to constantly reevaluate their strategies, how they use data and innovate, how they win customers and compete, and how they define their value proposition, says David Rogers, a professor at Columbia Business School and author of The Digital Transformation Playbook.

sap_Q316_digital_double_charted_images2“The traditional idea of putting up barriers to entry and creating a unique, sustainable competitive advantage is not a winning approach anymore,” says Rogers. He argues that tying value generation to meeting evolving customer needs means that executives must be open to making investments that serve this value.

The porous boundaries of the traditional auto industry illustrate this dynamic. Personal transportation is an evolving concept with a bevy of new players: smartphone-hailed ride services from the likes of Uber and Lyft; driverless cars backed by Google; and high-performance electric vehicles with software-based support services from Tesla. These disruptions have prompted a tide of investments from incumbents. As Reuters recently reported, Toyota will invest $1 billion over the next five years in artificial intelligence to enhance driver safety. GM has taken a $500 million stake in Lyft, according to Bloomberg. And Ford, like firms in banking, retail, and industrial manufacturing, has opened an R&D center in Silicon Valley.

Keep an Eye on the Exits

Rogers notes that transformation may also lead to divestments as companies pour their efforts into digital initiatives. He points to GE, which has been working to shrink its GE Capital unit as it beefs up investment in a new business devoted to services for industrial customers using analytics and the Internet of Things.Verizon, Rogers, adds, spun off the famous Yellow Pages business telephone directory business 10 years ago when it decided to invest heavily in its high-speed fiber optic cable network for television and internet services.

“The stock market was really annoyed,” Rogers says. But it was a good call because while the unit still had market value, it was not core to Verizon’s strategy. “That takes leadership,” he says. “‘This is a cash cow, but we can see this is declining in relevance to our market. We’re not going to turn it around, so let’s take money out of it while we can.’ And then they put it in a new opportunity to create value for customers and be a growing area for them.”

Today’s strategic choices involve the same criteria. “Looking to use digital technologies, through the lens of ‘How can I use this to create a new offering and additional value to my existing customers?’ sometimes opens doors to additional customers,” Rogers says. “And sometimes that involves building novel business models that are new to your company.” D!

How To Fix The Personalization Paradox


Customers are signaling that they want more personalized treatment from companies. In fact, a recent Accenture survey revealed that nearly 60% of respondents prefer real-time promotions and offers. That may seem like great news for marketers. But personalization strategies also come with risk.

Personalization creates more intimacy in the customer relationship, which can lead to more sales and loyalty. This promise of a tighter bond with customers has driven personalization to the top of marketers’ strategic agendas for 2016. However, this approach can threaten the most important aspect of the customer relationship: trust.

The tug-of-war over data

For personalization to work, brands need to gather detailed information about customers. But when asked whether they are willing to give up that information in return for more targeted products and promotions, many customers balk. Of the Accenture survey respondents, for example, only 20% were willing to reveal their location, and just 14% would consider parting with their browsing history.

This personalization paradox, as it is known, has been around for decades. But it’s going to become a bigger issue as digital connectivity increases and the data that customers generate through their activities—whether it be jogging with a Fitbit or refilling a fridge connected to the Internet of Things—outline their lives in ever-finer digital detail.

Complicating the situation, most customers aren’t very well-informed when it comes to data privacy. For example, a survey by the Annenberg School for Communication at the University of Pennsylvania found that 54% of respondents wrongly believe a website’s privacy policy means that the site would not share their information without their permission.

Focus on trust and value

How can companies reduce customer fear, ignorance, and uncertainty about personalization and privacy?Research has found that customers are more likely to take advantage of personalization from companies they trust and that offer them real value in exchange for their information.

It’s important to emphasize trust in the customer relationship because it’s at a low ebb. For example, just 7% of customers say the offers they receive from companies are consistently relevant. And 27% have said they’ve stopped visiting a website or mobile app after receiving irrelevant information or product recommendations.

Bonus: Learn how companies can create moments that matter to customers, anytime and anywhere in the white paper “Live Customer Experiences for the Digital Economy.”

In this kind of a climate, companies must demonstrate that they are worthy of customers’ trust before pushing too hard on personalization. Research has shown that there are two components of trust:

  • Confidence. Customers must believe that the company can provide a quality product or service.
  • Benevolence. Customers must believe that the company is willing to consider every customer’s self-interest above their own.

The benevolence aspect of trust is particularly important when it comes to personalization. In this regard, companies demonstrate benevolence by offering clear, understandable data collection and usage policies and by giving customers control over their information and how it is used. Customers are hungry for that control. A Pew Research Center survey found that 90% of those surveyed want to decide what information is collected about them.

Once trust is established, personalization has to offer real value. That value could come through useful services or discounts, for example. The key is to avoid stepping over the invisible line from cool to creepy, such as the time when Target sent coupons for diapers to an expectant teen before her father knew of the pregnancy.

Of course, the personalization paradox and online privacy are issues as big as the Internet. Customers will continue to fear for their privacy as long as data breaches continue and irrelevant and offensive offers continue to hit their inboxes. But focusing on trust is the beginning of a solution.

A Catalog of Civic Data Use Cases


How can data and analytics be used to enhance city operations?

What kinds of operations-enhancing questions have cities asked and answered with data and analytics? The catalog below is an ongoing, regularly-updated resource for those interested in knowing what specific use cases can be addressed using more advanced data and analysis techniques.

For examples that are currently being implemented in cities across the country, you can click to expand the question to see additional information about the solution.  All other examples represent potential questions that cities could work to address with data and analytics.

We welcome further submissions to the list by email.  Submissions can include either current examples of how cities are addressing specific operational or policy issues with data, or ideas for how to address issues that you hope cities will one day be able to answer.





  • Can we determine where unsafe housing problems are unlikely to be reported through 311?
  • How can we use analytics to prioritize accessibility inspections for building alterations, and make sure they are compliant with municipal building code and state accessibility requirements?
  • Who is most likely to be guilty of financial crimes and fraud?
  • How can inspectors reduce response time to maintenance complaints?
  • How can we prioritize annual elevator safety inspections?  For example, can we predict or identify which elevators pass every year and could be outsourced to a 3rd party?
  • How can we predict vacant or abandoned buildings before they reach that status?  To do so, can we use court foreclosure filings, US Postal “undeliverable” data, tax information, and data outside government, such as utility bill records?
  • Which construction / renovation projects are the highest risk / should be inspected first?
  • Which buildings are the highest risk / should be inspected first?
  • Which equipment (such as boilers, elevators, cranes, vehicles, etc.) is the highest risk / should be inspected first?
  • What variables affect inspector productivity and which can be most easily influenced? What distinctions can be made between inspectors who complete a high number of inspections and those who are at the bottom end?
  • Based on the relationship between inspections and violations, what building inspection regimens are most effective at preventing violations from occuring?
  • How many inter-agency inspections are conducted each year? Do they effectively detect current violations?
  • Which city debts are least likely to be paid?
  • Which taxpayers are least like to pay?
  • What city blocks need more inspection enforcement?
  • Which businesses are most likely to be violating weights and measures?
  • How can we determine what businesses will have over-occupancy issues, including multiple incidents of over-crowding?
  • How can we tap social media for information on illegal businesses?
  • What property owners, architects, developers, businesses and landlords need more regulatory enforcement?
  • How can we use social media to ensure licenses are conducting legal business?
  • Can we predict which stores sell cigarettes to youth?
  • How can we target stores that sell outdated food or expired baby formula?
  • Does the order of inspections (building, health, or fire) increase the rate of violation?

Profitability Analysis and CO with Simple Finance


This post will give the functionalities offered by Simple finance in COPA and management accounting

The long pending requirement from the majority of the customers in manufacturing industry is getting the COGS break up each head wise and it needs to post to a different GL account, in this way COPA is in sync with FI and it reduces the lot of reconciliation issues, the same issue has been addressed in simplified profitability analysis and it is part of simple finance.

In CO the main focus is to reduce the month end closing activities time and increase the system performance, In Sfin we have a separate set of transaction codes to perform this activity.

  • In simple finance, SAP is recommending for Account based COPA, account base in the default solution as the advantages of costing base has been incorporated in account base, as well enhancing the reconciliation aspect by having single document for Finance and COPA through universal journal entry, and improving the performance through the use of S/4 Hana database. No change in costing base approach.
  • The COEP, COSS and COSP tables are replaced with ACDOCA.
  • View tables are also available to reproduce the data in the old structure, for example V_COEP would allow seeing actual postings.
  • Assessments with in CO will update the COEP for CO documents and accounting documents with ACDOCA
  • Table ACDOCA would store both FI and CO posting in a unified document. As account based COPA posted is same as CO posting, the characteristic of account based COPA would also be part of ACDOCA



Configuration for splitting the cost of goods sold:

IMG: Spro > General Ledger Accounting (New) > Periodic Processing > Integration > Materials Management > Define Accounts for Splitting the Cost of Goods Sold

In Account Based COPA, there was no option to have a split of the Cost of Goods Sold into its components. This did not allow business to compare the component level costs of the inventory in terms of plan and actual, which can be basis of production re engineering. With Simple Finance, this option has been made available in account based COPA.


Configuration for additional quantities:

Spro > Controlling > General Controlling > Additional Quantities > Define Additional Quantity Fields

Additional quantity field can be configured. Badi FCO_COEP_QUANTITY has to be used.


In Simple Finance, the settings for Profitability Segment Characteristic is not supported any more, as each profitability segment contains all available characteristic values.


With Simple Finance, Integrated Business Planning would be in general used for overall Planning purpose. However planning available in account based COPA would continue to exist, as it exists before. But with additional flexibility IBP would be the primary Planning tool going forward.

For Reporting User Interface tools like Lumira would be used. This gives additional flexibility of query based reporting, real time value updation etc. However Ke30 reports can still be created.

With the simple finance, the benefits like reconciliation with financials, system performance, cost of goods sold and IBP is as follows.


I hope this post will give some inputs on COPA in simple finance, Happy learning and welcome your valuable comments.

Visit –

@ITChamps_SAP – Pure Play SAP Consulting Firm

Do You Have A Mobile Strategy?

Man using tablet computer at station

Mobility is a key strategic initiative for both consumer and B2B facing companies, as over two-thirds of the IT leaders Lopez Research surveyed listed mobile-enabling the business as a top priority in 2016. Yet, only 48% of the firms interviewed have a formal mobile strategy in place. This disconnect between crafting a mobile strategy and deploying mobile applications can dramatically decrease the effectiveness of a company’s mobile efforts. For example, a mobile strategy should define the architectural approach for connecting data from Systems of Record and engagement, such as ERP, CRM, and SCM, to mobile applications. Without this, the apps development team is building a pretty user interface that can’t connect to transactional systems.

Three Phases of Mobile Strategy

Most companies will evolve to mobile-empowered businesses in three phases that Lopez Research defines as extend, enhance, and evolve.

Phase 1: Extend existing apps to mobile

A majority of organizations, regardless of the presence of a formal mobile strategy, are extending a subset of existing applications to mobile devices today. In many cases, these are micro apps that offer a subset of the features found within PC applications. Examples of micro apps include approvals, expense reporting, and time tracking. During the initial stages of mobile enablement, many companies focus on delivering paper-replacement applications such as forms, price lists, and brochures. In this phase, companies are supporting only a few apps, and the issues associated with foregoing a formal mobile strategy aren’t obvious.

Phase 2: Advance capabilities of existing apps

As firms move into the second phase, IT is advancing the capabilities of existing apps by adding new functionality found in mobile devices such as image capture, bar-code scanning, and availability of location data. For example, retailers are improving in-store customer service with mobile information access and recommendations engines. Industrial industries are minimizing downtime by adding sensor data, such as temperature and vibration, to new mobile apps for plant managers. Across industries, organizations will be creating mobile solutions that use new data and device functions (e.g. camera, voice navigation, and location) to gain efficiencies and improve business with better information such as location data, voice-enablement, and image capture. It’s during phase two that companies realize they need a strategy to manage and secure mobile applications, scale mobile application development, and align with the business KPIs for digital transformation.

Phase 3: Focus on mobile to reinvent business models and processes

In the final phase of mobile-enablement, companies have already deployed foundation technologies such as enterprise mobile management, mobile application development platforms, and agile dev-ops processes. At this point, IT will focus on leveraging mobility as part of a toolkit to reinvent internal processes and transform business models. For example, product manufacturers are shifting to digital service models that couple hardware with subscription services accessed via mobile devices. Companies will offer contextual services by combining information such as location, device type, previous transactions, social media sentiment, and current process.

Create a clear mobile strategy

A mobile strategy, while its own entity, is also a critical part of a company’s overall digital transformation strategy. Mobile technology provides new contextual elements such as location, sensor data, and image-capture information that can enhance business processes. It also introduces new design paradigms such as touch and voice navigation. These attributes, coupled with the portability mobile provides, are key enablers of transforming digital business processes.

The mobile strategy should be interlaced with other IT initiatives such as cloud computing, data processing, and analytics strategies. As companies look to build new mobile applications, the cloud can provide many mobile services such as a development and testing environment, cloud-based mobile application middleware and development tools, as well as Analytics-as-a-Service capabilities. Additionally, companies can look to cloud-resident SaaS applications to deliver mobile applications that operate seamlessly on the latest mobile devices. Mobility can deliver both efficiencies and competitive differentiation if IT and the line of business managers come together to build a strategy.