Products-People-Digital Equilibrium

With Prof. Michael Porter

With Dr. Michael Porter

I am writing this blog post to bring out the essence of our discussions that occurred during the”FT-PTC Future of Industrial Innovation Global Series” organized in New York yesterday. Manufacturing industry thinktank and senior leadership personas have come together to exchange ideas on how manufacturers are adopting new-age technologies to compete.

A joint keynote address from Dr. Michael Porter and James Heppelmann (Jim), CEO of PTC, was an excellent “confluence of thought” that brought together strategic mindset and technology acumen.

While the siloed productivity of human and machine/product has been evolving over decades, the Digital technologies are offering capabilities that can enable progress to the global optima and excellence creating Human-Machine/Products-Digital Advantage. Machine and Products are interchangeably used from now on in the context of manufacturing.  The connection between Products/Machine and Digital (Cloud, Digital Twin, etc.) has been established for some time. This connection enables sensing of a product’s data by digital technologies (edge/embedded) or digital controlling through the optimization of products/machines. But there is a lag between the human-machine and the human-digital connection compared to the digital-machine connection. This lag is causing the “discontinuity” of humans in human-machine-digital ecosystems.

Prof. Porter elaborated on the manufacturing evolution to date as shown below. His vision of the next phase in the evolution is “Smart Connected People”. He emphasized that this phenomenon is happening now with progress from connected products (IIoT) to Smart Connected People with the advent of Augmented Reality (AR) on occasions combined with Virtual Reality (VR) and Xtreme Reality (XR).

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Today’s interfaces separate the physical and digital worlds. A prime example being the GPS system in the car. The 2D display on the GPS shows directions, but human cognizance has to take that input, process it, and finally execute it. This 2D to the 3D gap is what Dr. Porter referred to as “Cognitive Distance” which results in “Cognitive Load”. Imagine a “Heads Up” display leveraging AR that minimizes and eliminates the cognitive distance and cognitive load. AR narrows the cognitive distance by integrating the Digital world into the Physical world, seamlessly.

Digital transformation is leapfrogging the industrial and manufacturing progress continuum from Monitor -> Control -> Optimize to “Autonomy”. AR technology is uplifting the human connection by enabling visualization and collecting the instruction to pass on to the machine. Technologies like computer vision are promoting the human-machine interaction such that the embedded software & systems are allowing humans to diagnose the inner workings of products which were an earlier limitation. In scenarios where AR gets dangerous, VR can fill the gap with simulations and move forward. Thus, the Human-Machine-Digital equilibrium is being established to drive the next-level of industrial innovation.

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Prof. Porter’s strategic foresight was well complemented by Jim’s real-world technology development and use cases. New-age digital technologies are expanding industry boundaries through precision agriculture and smart city solutions. In the past, products progressed to smart products and then became connected smart products but the present and future of industrial evolution revolve around “product System” and “System of Systems”. All-in-all it was great mindshare on today’s manufacturing excellence. I am parking the detailed description of use cases to my next blog post.

P4 I summarize this post with two important closing thoughts from Dr. Porter and Jim.

  1. AR enables People as IoT enables Assets/Products
    • Enabling more effective training and guidance to address the shortage of skilled front-line workers
    • Enhancing worker productivity through better collaboration with machines
    • Counterbalancing the shift to automation by empowering human workers
  2. Both IoT and AR combined to change the competitive environment, requiring new strategic choices and organizational models. For example,
    • Technology development: internal or outsource?
    • Disintermediate distribution or service channels?
    • change the business model?

In the end, I interacted with Prof. Porter to reflect on the discussions of the day and sought his expert comments on the man-machine inflection point. Here is the gist of my discussion. Over the past decades, the industry experienced a gradual reduction in annual work hours, resulting in the gradual improvement of productivity and output. One key attribute of productivity is man-machine collaboration. With digital technologies, the man-machine inflection further uplifted the productivity to 2X, 4X and in the panel discussion yesterday, one company executive was mentioning about 9X productivity gains. In view of this, my questions were,

  • Where does the productivity multiplication (constant uplift of human-machine combined productivity/inflection point) lead next?
  • In the near future, is it going to be survival of the fittest between a human vs machine as the trend line of annual working hours continue to decline?
  • In the long term, would machine constantly chase & replace the humans or the cognitive distance prevail in the foreseen future?

I will follow up with Dr. Porter on this and share further learnings. Stay tuned!!

Internet of Medical Things (IMoT)

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Many healthcare firms and consumers have latched onto the Internet of Medical Things (IMoT) by way of wearables, such as FitBits and Garmin watches, referred to as “FitTech.” With over 2/3 of medical devices estimated to be connected over the next 3 years, IMoT is going to have a significant impact in Healthcare operational and financial processes. Let us examine the impact of IMoT on healthcare payers, health providers, and consumers.

A) IMoT and Payers: 

i) Underwriting: The first process comes to mind is Underwriting. By equipping consumers with IoT-enabled medical devices underwriters can better understand what an individual’s health looks like daily, rather than at long historical intervals. With this wealth of information at the helm for an individual, underwriters gain access to health data from periods of time that used to be non-existent in health records and claims. IMoT can enable underwriting for

  • improved bottom-line of the payer by better understanding what each individual new member will cost them
  • increased wallet share by preventing lower-risk members from being improperly marked as high-risk based on one-off health encounters
  • Optimized underwriters’ time spent on due diligence, especially avoiding unnecessary full medical underwriting (FMU.)

ii) Preventive Care: Preventative care is a perfect application of IoMT. Biometric sensors and other devices can collect real-time data from health plan members, help point to higher-risk metrics or lifestyle choices, and notify payers to get the correct members enrolled in prevention programs. Oe successful use case is Beam Dental. The Beam Brush tracks an individual’s tooth brushing habits (such as the dental habits of employees under their employer’s insurance plan) and allows their good habits to drive down the cost of dental insurance for their group. By activating members to take control of their health before chronic or acute health issues arise, payers will see success in loss prevention as well as a happier (and healthier!) member base.

iii) Claims and billing efficiencies: IoT can aid in cumbersome tasks that waste administrative hours by leveraging AI led solutions, such as determining whether a claim should be accepted or rejected for minor claims or processing payments. By freeing up administrative time from these tasks that can be automated, payers can invest more in programming for their members to drive focus towards prevention leading to savings in administrative costs and savings in claims payments from healthier members.

B) IMoT and Providers:

IMoT has the potential to facilitate remote patient care to optimizing hospital operations to streamlining data management, healthcare providers can leverage the lucrative potential of IoT. These use cases are elaborated below.

i) Improved hospital operations: IMoT can be introduced and ramped up to optimize a hospital’s daily functions and cut unnecessary costs. Tracking medical assets within a facility is a good use case. Every year, millions of dollars bleed from hospitals from lost or stolen equipment. By attaching sensors (e.g., RFID or Bluetooth) to equipment, hospital staff can track the exact locations at any point in time, allowing for better oversight. This can solve the problem of lost equipment, reduce theft, and even track overall use of equipment. The life of medical equipment varies greatly based on the frequency of use. By tracking movement over the life of a piece of equipment, hospital administration can get a better idea of when to replace or schedule maintenance to avoid periods of time where equipment is unusable.

A second IMoT use case is in intake or discharge processes. With IoT, unobtrusive sensors can be placed in patient wristbands and staff badges better to track how quickly patients flow through different areas of the hospital (such as pre-op rooms to the operating room) or how efficiently staff attends to a given patient. This can remove backup from current bottlenecks in flow at the hospital, including but not limited to Emergency Department wait times, intake, discharge, and shift changes.

ii) Interoperability and Data Monetization: IMoT at a basic level improves existing systems for providers. For example, biometric devices and sensors are often system-agnostic and can connect through APIs to multitudes of EHR systems. If a patient has doctors in multiple health systems, their disparate EHRs (and therefore doctors and care plans) can be updated accordingly. The IMoT combined with AI/ML and NLP can nurture the massive loads of HC data. By relying on IoT-enabled technologies, providers will no longer deal with unusable, unstructured data but rather well-organized and insightful data systems. The world of well-managed data in hospitals and health systems opens up with the adoption of forward-thinking technology. Doctors can better tailor care plans to patients’ specific needs based on historical data of like patients and avoid oversight of potential complications such as contraindications.

iii) Expanding remote care revenue streams: IoMT eases the implementation of remote patient care. With IMoT doctors can help patients purchase and set up remote equipment to measure biometrics, provide care, and talk face-to-face over the internet i.e. telemedicine. Doctors then are able to receive the data they need to adequately modify care plans without requiring a patient to walk into the office as well as have more frequent communication and therefore a better understanding of a patient’s day-to-day health status. IoMT not only allows for better continuous care but also boosts patient satisfaction and engagement. Patients that spend more face time with their providers tend to have better relationships and therefore better patient satisfaction—a critical component of healthcare with more and more models shifting to value-based reimbursement from health payers.

IMoT implementation roadmap:

While the Internet of Medical Things has the potential to fuel HC growth, IMoT implementation sought to be a rocky path. But approaching IMOT implementations with a pragmatic approach leads to a better navigation path. Let us evaluate some basics steps of IMoT roadmap.

  • Identifying Healthcare organization business goals to build IMoR ecosystem
  • Develop a viable and convincing business case to roll-out IMoT
  • Next coming up with a clear vision and goals to realize with connecting medical devices
  • Big-Bang approach may lead to burn-out, and hence identify pilots or PoCs od IMoT success areas
  • Take an iterative approach to reiterate the ideation process and move forward with an implementation initiative

Sounds generic! That is the stepping stone for IMoT implementation. Imagine that healthcare companies manufacture more than half a million different types of medical devices, including wearable external medical devices like insulin pumps, blood glucose monitors, etc, implanted medical devices – implantable cardioverter defibrillator devices, and stationary medical devices – scanning machines, etc. to name a few. Most patient interactions with the HC system involve the use of medical equipment and devices. IMoT brings these interactions to life. Hence taking an incremental approach is the only way forward.

The true implementation of IMoT involves, “developing an in-depth understanding of end users”, “defining funding, business and operating models”, “clearly understand device interoperability requirements”, “embed security at the core”, “ensuring regulatory compliance”, “more importantly attract talent and build digital capabilities”, “improve the adoption of medical technology at scale and with trust”, and finally “create an ecosystem of seamless partnerships”.

IMoT Solution Providers:

Colleagues on this forum have highlighted many advantages of IMoT like cutting emergency room wait times, remote health monitoring, ensuring critical equipment availability, improved drug management, optimized staffing and workflow, better diagnoses, better outcomes with fewer false alarms, etc. As IMoT value proposition is gaining more traction, many solution providers are offering products and solution to tap this value.

With an estimated market value for IMoT technologies >$150 billion in over next 3 to 4 years, Philips, Siemens, GE Healthcare and Medtronic are currently leading IoMT technology investments, with Philips primarily dealing with cardiac monitoring, remote patient communication devices and sensor-related products, and GE and Medtronic instead focusing on cloud-based technologies in existing monitoring devices, implants, and cardiac pacemakers.. Listing below few examples.

  • IMoT and Telehealth: Health Net Connect offers various remote patient monitoring packages that monitor conditions like CHF, COPD, diabetes, and hypertension with devices like BP/BG monitors, Handheld ECGs, pulse oximeters and spirometers. Not only is this technology leading to reduced costs as patients handle everything in-house, but by eliminating the need to visit health professionals and vice versa, it’s also improving their overall patient experience.
  • IMoT and Drug Management: Proteus Discover is a health company that measures medication treatment effectiveness and helps physicians improve clinical outcomes and patients reach health goals through sensor-embedded pills like the one mentioned above. Once the ingestible sensor-containing pill reaches the stomach, it sends a signal to patch the patient is wearing, which monitors each time a pill is taken, as well as their general rest and activity patterns. another example is, Abilify MyCite approved by the U.S. by the Food and Drug Administration
  • IMoT and Medical Device Monitoring: e-Alert from Philips are also ensuring that critical hardware is always accessible, and if something like a breakdown does happen, staff members will be immediately alerted.
  • Siemens IoT solutions for the medical device industry are powered by combining big data with digital twins, a virtual representation of actual devices, moving in tandem across the lifecycle and connected by digital threads. By connecting virtual development and production planning environments with real support and lifecycle production data, Siemens equipping med-tech organizations with the transparency and advanced analytic tools required to gain a competitive edge using big data.
  • eVisit is a telemedicine platform that enables doctors to conduct examinations and prescribe remedies for their patients by remote.
  • Amiko.IO focuses on providing products for respiratory disease management, complete with an AI-powered platform.
  • InfoBionic’s MoMe Kardia provides remote monitoring of cardiac arrhythmia.
Challenges implementing Healthcare IoT / IMoT:

HC firms have to overcome a few key challenges ranging from data security to legacy infrastructure that may hinder health care IoT initiatives. Alongside these evident challenges, IMoT should address the following areas for widespread adoption.

  1. Health data explosion and sensitivities: HC is one the largest sector contributing to massive data creation. HC organizations to use IMoT technology effectively have to address growing data storage needs. As well HC has to be exceptionally careful to treat patient data from IoT devices according to federal and state regulations. The flood of data created by the IoT gadgets and devices used in the HC industry could also cause unforeseen problems if organizations are not equipped to handle it properly and verify its quality.
  2. Lack of EHR system integration. While the data that is collected from IMoT devices can include a patient’s vital signs, physical activity that information does not typically travel to an EHR system and, in most cases, is not centralized or made easily available to providers. This limits the information’s value since it is not always presented to the provider in a clinical context.
  3. An increase of available attack surfaces with IoT devices: IMoT devices explosion in health care present concerning vulnerabilities as device use rises, so does the number of ways hackers could infiltrate the system and mine for the most valuable data. Hackers could potentially learn about how a connected medical device operates by getting into the system and reading its error logs. The knowledge the hackers gain could facilitate breaking into a hospital network or making devices publish incorrect readings that influence patient care. It is high time for vendors, providers, and manufacturers’ to collaborate to reduce patient risks by closing the gaps that can form between the layers of an IMoT system by reinforcing standards and normalizing secure protocols. It’s not possible to know all the cybersecurity risks health organizations may face. Nonetheless, facilities planning to implement IoT technology must take care to increase awareness of existing threats and understand how to protect networks and gadgets from hackers’ efforts.
  4. IMoT data in silos due to interoperability challenges: Patients are likely to collect different sets of data when using different medical devices depending on each device’s purpose and, in some cases, the ordering physician. IMoT data alone may not be as meaningful if it is not within the context of a full health record. With the lack of wider adoption of adequate interoperability, data from different IMoT devices may remain locked in each individual system and lose its potential value to the rest of a patient’s care team.
  5. Data security causes concerns in the IMoT implementations: From the time that the data is collected at the device level to the point that it is transmitted over to its final destination, securing that information is critical and is required under HIPAA. But with the lack of common security standards and practices, many health IT professionals have concerns about the risks associated with IMoT device tampering and data breaches.
  6. Plan for ecosystem needs to be successful: According to a recent Cisco survey, ~60% of projects encounter trouble at the PoC stage or shortly thereafter. The study suggested that utilizing external partnerships (e.g. platforms) was a crucial factor for those organizations that achieved successful implementations. When it comes to the starting small and prioritizing projects that align with their most prominent business objectives or patient needs is key to the success.
  7. Overcoming legacy infrastructure challenges: Outdated infrastructure is a known fact in HC. Even though retrofitting can breathe new life into aging infrastructure, truly taking advantage of IoT is tricky if a facility’s infrastructure is outdated. Hence using IMoT in ways that make sense for the needs, budgets, and infrastructures of HC organization and having robust plan to ramping up resources to fill the gaps is the key to the success of IMoT implementations.
  8. Stringent high availability and near-zero tolerance for failure: One of the common use of IMoT technology in HC is to apply it to patient monitoring systems. While it is handy to take that approach, unlike other IT systems (ex: websites), these devices typically cannot go through planned periods of downtime. Hence, updates have to occur seamlessly as people use the monitoring devices. For the hospitals to depend on IMoT-enabled supply cabinets to track resources reducing inventory management issues, IMoT devices devices are to be audited correctly eliminating human errors.

The Changing Role of Retail Workforce

I was visiting Lush – a fresh handmade cosmetics store along with Lush_app.jpgmy daughter and felt that the shopping experience compared with the past is changing in a noticeable way, in particular when it comes to interactions with the store workforce. I came to know that Lush employees typically go through extensive training to ensure they have the tools and knowledge to deliver this kind of service. At Lush the digital technology offers a replacement to the information usually found on packaging – the Lush Lens app uses machine learning to recognize products, meaning customers can simply scan ‘naked’ products to discover key information about them. Hence the retail workforce is upskilling to add value beyond the digital offerings.

This blog post is a result of the experience above. Global Retail and e-commerce leaders reimagining their business models in digital evolution and which is further changing workplace practices. I can say from my vantage point that digital, social and environmental developments are shifting the needs of the retail workforce. It is evident that device and sensor proliferation is aiding retailers to experiment intelligent and connected methods to innovate new business models to try new markets, offer new services and create rich & compelling customer experiences. The new-age developments listed below reflects the continuous transformation of the retail workforce

  1. Knowledgeable workforce offering personalized shopping experience: In a world where just about any product or service is instantly available online, shoppers visit a physical location is driven by specific needs. It means recognizing that shoppers would make the trip because they need something more than what they find in the digital world: face-to-face contact, empathy, and deep expertise. Whether they want to figure out how to hook up a smart home, what dress to wear to a formal dinner, or what to pack for that dream wilderness vacation, they want to talk to someone who can offer them more knowledge and personal understanding that they can find with a quick online search.
  2. Fitment of the retail workforce in experience economy: Stores just can’t be product-fulfillment centers. In both the physical and virtual worlds, product fulfillment is fast becoming the domain of AI and robotics, with retailers, consumer products companies and e-commerce platforms racing to develop the best systems to anticipate consumer needs and deliver products to meet them. What technology cannot fulfill, however, are human needs that remain unmet today and will continue to evolve in the future. One thing I’ve learned through my work is that as technological connections grow, so does the human need for meaningful connections. This need is what’s driving the experience economy. Whether in restaurants, travel groups, shared workspaces, yoga studios or spin classes, people are actively seeking intimate connection with other people and finding it in spaces and communities like these.
  3. Uplifting workforce skills is the need of the day: Process improvement, speed, and efficiency are at the core of successful online businesses. With online infiltrating over to brick-and-mortar sales it’s a mismatch in areas such as supply chain, inventory management, trend identification, competitive pricing analysis, etc.; for example, the ability to automate 99% of pricing decisions, not only offers a real-time advantage, but it also eliminates hours and hours of manual work per week. Hence the use and mastery of algorithms is a key tool of the buyer in successful online companies, a skill that is not as prevalent in brick and mortar;

With the advent of modern technologies bringing e-commerce intelligent systems that make running a retail store more efficient, my experiences with retailers progressed on leveraging in-store data. Having the right retail workforce management solution can take care of tedious administrative tasks across the board, while simultaneously collecting data to instantly improve in-store operations. With this schedule, store managers can be confident knowing that the most knowledgeable and high performing sales assistants are on the shop floor during times of high customer traffic, enhancing the shopping experience and resulting in more sales.

As retailers continue to evolve in experience economy continuum, it’s the value that a capable retail associate can add – the expertise, social sensitivity, and problem-solving skills – that will differentiate the good stores from the bad, the stores that will endure from those destined to fade from the scene.

Monetizing IoT Data with Blockchain

IoT Data

“Data is the most important asset class of current generation”. In Internet of Things (IoT) era, with increasing device proliferation in hyper-connected world, humongous collection of sensor data can facilitate the conversion of incredible ideas into value-adding services. In creating value with data explosion, Blockchain Technologies can play a critical role creating a peer-to-peer marketplace providing IoT sensor owners an opportunity to monetize data and simultaneously enable data consumers with a decentralized market to buy IoT sensor data.

According to Allied Market Research (AMR), the global market of sensors is poised to grow with a compound annual growth rate (CAGR) of 11.3 percent until 2022 when the market would reach $241 billion. The data resulting from such vast reach of IoT sensors is for the primary usage of the sensor owner or it is enhanced with value-added insights and reselling. In both the scenarios of either for primary usage or for enrichment and re-sale, the data remains unacceptably under-utilized and the utility if hindered away in organizational silos. Blockchain can provide a marketplace for IoT sensor data connecting data owners with 3rd party data consumers directly by externalizing the data outside primary silos.

The upside potential arrives from expected growth of todays 10+ billion sensors deployed globally to reach 40+ billion by 2020. Blockchain technology can help monetizing data by creating a marketplace offering a fully built financial ecosystem with a very minimal fees compared to a traditional fiat payment processors who typically charge between 1 and 3% for transactions. Also with creation of data utility tokens offers possibility to use small fractions of the token combined with very low fees making micro-transactions feasible. As well decentralization with blochchain backbone enables a very large numbers of participants in a trustless environment transacting with each other.

As shown in the picture above, a perfect ecosystems can be built for monetizing IoT data with Blockchain technology backbone. The players include sensor owners, data lakes gets created, network providers, blockchian data broker framework, data processers/enrichers, and data consumers / buyers. Sensor owners get an opportunity to monetize their data recovering some of their investments in IoT sensors. Network operators can win-back their enterprise accounts gaining scale and speed in the adoption of their network. This creates new types of buyers offering ease of access to data. Alongside data processors gain an eco-system to sell their services to the right people.

The use cases for such monetization of IoT data can be numerous covering multiple industries. A few examples of described below.

Use case

Predictive Maintenance Value for Process Industries

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Process industries are undergoing digital transformation building and integrating Minimum Viable Products (MVPs) in their strategic path to enabling business models, services, customer experience, operations, and workplaces re-imagination. What I notice across process industry segment is application of industrial internet concepts in creating predictive maintenance models that are yielding advantages including – greater machine availability, superior process quality, easier to plan service intervals, longer machine service life, safer and more sustainable operation, lower service efforts and decreased costs. I am highlighting few aspects demonstrating thought leadership in this space.

  • Companies are sponsoring proof of concepts and pilots for creating models to monetize predictive maintenance. As Predictive Maintenance and Condition Based Monitoring directly impact equipment uptime, by offering Predictive Maintenance as a service, the manufacturer can guarantee equipment uptime to their customers for a fees, i.e. selling value-added services which promise recurring revenue.
  • Process manufacturing is leveraging integrated utilities to reducing electricity consumption with just-in-time energy management with a dynamic platform delivering energy performance improvement with ‘as-a-service’ through edge connectivity of various assets, data acquisition and gateway, cloud-based technology, and analytics. Also include tracking people movement and asset utilization.
  • SRP performance monitoring center using Industrial Internet is another classic example. Since starting the GE Digital’s SmartSignal program in 2012 and through to 2016, SRP identified more than 1,900 issues, of which 800 were “catches” – a problem that the plant was not previously aware of and, with the new alerts, was able to take corrective action. With time and improved training of the algorithms, the rate at which the company identifies true issues and catches has improved.
  • One use case of specific interest to Food and Pharma industry’s glass packaging quality control and improvement is Wi-NEXT IIoT that drives major changes in glass container quality improvement reducing non-conforming products by 7%, which equals 5% extra line productivity, better process control, and higher customer satisfaction
  • Lastly sustainable business models of predictive maintenance includes – bundling within basic service agreement framework, a freemium offering during warranty with downstream revenue potential, offer value added service with pay-per-use model, and gain-sharing with partner ecosystem.

Process manufacturing winners are those who identify best in class practices for developing business models for predictive maintenance of equipment. Win-win scenarios for manufacturers arise from enabling collaboration of experts in this space to exchange ideas, spot trends and drive innovations.

Pragmatic solution for data-age

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300 hours of video are uploaded to YouTube every minute! Almost 5 billion videos are watched on YouTube every single day. This is one example of the pace of data growth and overall size of data is piling into zetta-bytes faster. Where am I going with this is relevance of rapid analysis of data measured in hours or days rather than the stereotypical months of traditional data mining. The result is an opportunity to derive meaningful insights to business with more emphasis on predictive analytics.

Predictive analytics is nothing new. Predictive analytics is a way to identify the probability of future outcomes based upon historical data. For example, from customer perspective, companies can predict a likely lifetime customer value or the probability of either loyalty or churn. Let us look at few use cases to examine the relevance and importance of predictive analytics in the world of enormous data.

A fashion retailer story: Predictive analytics helped in analyzing the campaign spends and predicting incremental campaign impact of spend. This helped the retailer in understanding where not to spend: Having a close look predictive analytics helps in understanding the relationship between customer segments and the marketing campaigns being interacted with. This retailer predicted the probability of a particular channel influencing online or offline purchases within specific customer segments, and while this was enormously useful in understanding how to spend budgets targeting more personalized digital campaigns, it was equally insightful into identifying spend that wasn’t contributing to incremental value. The power of predictive analytics came in determining, should the retailer pay for this ad, or will a sale happen organically through another channel or communication that might cost nothing or next to nothing? This allowed the marketing team to choose the right channels to most effectively and efficiently reach different groups of prospects and customers, and second, it provided the information required to personalize by sending the right content and message to the right segments at a very granular level.

Preventing hospital readmissions: Hospitals are turning to predictive analytics as they began to feel the financial pinch of high 30-day readmission rates. Real-time EHR data analytics helps hospitals cut readmissions by five to seven percent. This demonstrates how predictive analytics in real-time can analyze EMRs data to automatically identify and target patients at the highest risk of readmission early in their initial hospitalization when there is a lot that can be done to improve and coordinate their care, so they will do well when they leave the hospital. Notably, Kaiser Permanente has been working to refine its readmissions algorithms in order to better understand which returns to the hospital are preventable and which are not, a crucial distinction for value-based reimbursements.

Lifetime value analysis of a subscribers of communication service providers: CSPs are lately realizing that not all customers are the same. It is important for CSPs to assign a quantifiable dollar value to each customer, in order to prioritize various sets of customers. The Lifetime Value of a subscriber provides the predicted yield from each customer over the customer life. This helps CSP in offering high priority customers loyalty bonuses, preferential treatment through personalized service, better credit norms etc.
We are living in a world of data overloading. Predictive analytics can be a true human partner from elections to sporting events to the stock market on what the future will bring. Predictive analytics elevate human kind from an educated guess to data backed decision.