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LinkedIn Best Companies To Work For In 2022 Dominated Again By Tech

LinkedIn

Amazon’s Sunnyvale, CA Campus (source: Istockphoto)

  • Tech leaders are six of LinkedIn’s top ten companies to grow your career in 2022.
  • Amazon is the again highest rated company, followed by Alphabet (2nd), IBM (6th), AT&T (7th), Apple (9th), and Comcast (10th).
  • 19 of the 50 top companies in the U.S. are in the tech industry, including Dell, Intel, Oracle, Salesforce, Cisco, and others.
  • LinkedIn identified four key trends in their analysis, with flexible work is becoming table stakes for recruiting and retaining employees.

These and many other insights are from LinkedIn Top Companies 2022: The 50 best workplaces to grow your career in the U.S., published today. All 50 companies are currently hiring and have over 530,000 jobs open across the U.S, with over 70,000 being remote positions. The LinkedIn analysis of the best companies to grow your career spans 35 global markets, including the U.S., Canada, Mexico, Brazil, Argentina, Colombia, Chile, Ireland, France, Switzerland, Austria, Germany, Israel, Italy, Spain, the U.K., Sweden, Belgium, Denmark, the Netherlands, Portugal, India, Japan, Singapore, Philippines, Malaysia, Indonesia, Australia, New Zealand, UAE, Egypt, Saudi Arabia, South Africa, Nigeria, and Kenya.

LinkedIn’s Top Companies 2022 spotlights the organizations investing in employee success and career development. LinkedIn’s methodology and internal analysis ranked companies based on seven pillars that display career progression: ability to advance, skills growth, company stability, external opportunity, company affinity, gender diversity, and educational background.

The 19 Best Tech Companies To Grow Your Career In 2022

The following are profiles of the top 19 tech companies hiring in the U.S. today with links to available positions accessible via LinkedIn:

Amazon

Amazon is the parent company of Whole Foods Market, Zappos, Twitch, PillPack, and others.

Global headcount: 1,600,000 (with 1,100,000 in the U.S.) | Top U.S. locations: Seattle, San Francisco Bay Area, New York City | Most notable skills: Warehouse Operations, Data Entry, AWS Lambda | Most common job titles: Software Engineer, Fulfillment Associate, Warehouse Associate | Largest job functions: Operations, Engineering, Program and Project Management | What you should know: Even as the country’s second-largest private employer, Amazon continues to compete in recruiting and retaining top talent amid a competitive labor market. The company recently announced that it’s doubling its maximum base salary for corporate and tech workers, and it raised average wages for warehouse workers late last year, increasing pay for more than half a million of its employees. But the e-commerce giant is going beyond compensation, too: investing $1.2 billion over the next three years to expand its education and skills training initiatives. Amazon now pays 100% of college tuition for frontline employees as part of its Career Choice program and covers high school diploma programs, GEDs, and English proficiency certifications.

See jobs at Amazon

Alphabet

Alphabet is the parent company of Google, YouTube, Fitbit, Waymo, Verily, and others.

Global headcount: 156,000 | Top U.S. locations: San Francisco Bay Area, New York City, Seattle | Most notable skills: Video Editing and Production, Google Cloud Platform (GCP), C++ | Most common job titles: Software Engineer, Program Manager, Product Manager | Largest job function: Engineering, Information Technology, Program and Project Management | What you should know: It’s been a big year for Alphabet: The company onboarded nearly 6,500 employees last quarter and saw significant growth across Google’s Cloud service and YouTube (whose revenues are now growing at a faster rate than Netflix). For those interested in flexibility, the tech giant has a robust offering. In addition to adopting a hybrid work model, the company told LinkedIn that Alphabet offers four ‘work from anywhere’ weeks per year, sabbaticals for long-term employees, and ‘no meeting’ days. But Alphabet has also worked to maintain a collaborative culture and support career growth while working remotely. Employees can take advantage of resource groups like Women@Google and its Googler-to-Googler training, which lets its workers get first-hand knowledge across different fields from other employees.

See jobs at Alphabet

IBM

IBM is the parent company of Red Hat, SoftLayer Technologies, Truven Health Analytics, and others.

Global headcount: 250,000 | Top U.S. locations: New York City; Raleigh-Durham, N.C.; San Francisco Bay Area | Most special skills: Kubernetes, Openshift, Hybrid Cloud | Most common job titles: Software Engineer, Project Manager, Data Scientist | Largest job functions: Engineering, Information Technology, Sales | What you should know: The perennial IT giant has re-upped its benefits offerings amid the Great Reshuffle, IBM told LinkedIn. The new initiatives are increased paid time off, more promotion and pay reviews, backup dependent care, virtual tutoring, and ‘compassionate leave’ for parents who experience stillbirth or miscarriage. In addition, as the company moves forward with a hybrid working model that allows employees to decide how often they want to be onsite, IBM has also transformed its onboarding process with “a focus on empathy and engagement” to help remote new hires feel more connected.

See jobs at IBM

AT&T

AT&T is the parent company of DIRECTV, WarnerMedia, Cricket Wireless, and others.

Global full-time headcount: 202,600 | Top U.S. locations: Atlanta, Dallas, New York City | Most notable skills: Design Thinking, Customer Experience, Futurism | Most common job titles: Retail Sales Consultant, Client Solutions Executive, Customer Service Representative | Largest job functions: Sales, Information Technology, Engineering | What you should know: Just three years after the acquisition of Time Warner, AT&T is changing course. The company agreed to a deal last year that will combine WarnerMedia’s assets with Discovery’s to create a new, separate global entertainment giant. Once the spinoff is completed (likely mid-2022), the telecom company will be focused on its core business — expanding access to broadband internet. For its employees, AT&T offers several advancement opportunities. For example, it invests $2 million annually in ‘AT&T University,’ an internal training program to help its workers upskill, and has partnered with groups like Udacity and Coursera to offer advanced online courses.

See jobs at AT&T

Apple

Apple is the parent company of AuthenTec, NeXT Software, Shazam, and others.

Global headcount: 154,000 | Top U.S. locations: San Francisco Bay Area; Austin, Texas; New York City | Most notable skills: Apple Software and Hardware, Technical Learning, iOS | Most common job titles: Software Engineer, Technical Specialist, Mac Genius | Largest job functions: Engineering, Information Technology, Sales | What you should know: Apple is increasing benefits and pay for retail workers to attract and retain employees at its 270 retail stores across the U.S. — including doubling sick days for both full-time and part-time employees and granting more vacation days. Its retail employees are also eligible for paid parental leave and can access discounted emergency childcare. In addition, after being one of the first companies to tell its corporate employees to work remotely in March 2020, Apple is now asking that they return to the office three days a week.

See jobs at Apple

Comcast

Comcast is the parent company of NBCUniversal, Sky, DreamWorks Animation, and others.

Global headcount: 189,000 (with 130,000 in the U.S.) | Top U.S. locations: Philadelphia, New York City, Los Angeles | Most notable skills: Media Production, Cable Modems, Broadcast Television | Most common job titles: Software Engineer, Communications Technician, Salesperson | Largest job functions: Engineering, Sales, Information Technology | What you should know: Comcast prioritizes career growth and development among its employees through various benefits — including mentorship programs, department rotations and tuition assistance for continuing education and skills development. As a part of its commitment to wellbeing, it also pays for 78% of its employees’ health care costs. Want an in? Comcast says the #1 skill it looks for in new hires is authenticity. “We believe that by being yourself, you are empowered to do your best work,” the company told LinkedIn.

See jobs at Comcast

Meta

Meta is the parent company of Onavo, WhatsApp, Instagram, and others.

Global headcount: 71,900 | Top U.S. locations: San Francisco Bay Area, Seattle, New York City | Most notable skills: PHP, Program Management, Social Media Marketing | Most common job titles: Software Engineer, Technical Recruiter, Data Scientist | Largest job functions: Engineering, Information Technology, Human Resources

See jobs at Meta

Dell Technologies

Dell Technologies is the parent company of Dell EMC, SecureWorks, and others.

Global headcount: 133,000 | Top U.S. locations: Austin, Texas; Boston; San Francisco Bay Area | Most notable skills: Software as a Service (SaaS), Kubernetes, Salesforce | Most common job titles: Account Executive, Software Engineer, Inside Sales Representative | Largest job functions: Sales, Information Technology, Engineering

See jobs at Dell Technologies

 Accenture

Accenture is the parent company of Karmarama, The Monkeys, Fjord, and others.

Global headcount: 674,000 | Top U.S. locations: Washington D.C., New York City, Chicago | Most notable skills: Amazon Web Services (AWS), Management Consulting, Software Development Life Cycle (SDLC) | Most common job titles: Managing Director, Management Consultant, Business Integration Manager | Largest job functions: Information Technology, Business Development, Engineering

See jobs at Accenture

 Verizon

Verizon is the parent company of GTE Corporation, MCI Communications Corporation, and others.

Global headcount: 119,400 (with 105,800 in the U.S.) | Top U.S. locations: New York City, Dallas, Washington D.C. | Most notable skills: Quotas, Wireless Technologies, Solution Selling | Most common job titles: Solutions Specialist, Customer Service Representative, Business Account Manager | Largest job functions: Sales, Engineering, Information Technology

See jobs at Verizon

 Intel

Intel is the parent company of Mobileye, Data Center Group, and others.

Global headcount: 121,000 (with 55,700 in the U.S.) | Top U.S. locations: Portland, Ore.; Phoenix; San Francisco Bay Area | Most notable skills: JMP, System on a Chip (SoC), Statistical Process Control (SPC) | Most common job titles: Software Engineer, Process Engineer, System-on-Chip Design Engineer | Largest job functions: Engineering, Operations, Information Technology

See jobs at Intel

Oracle

Oracle is the parent company of MICROS Systems, NetSuite, Peoplesoft, BEA Systems, and others.

Global headcount: 133,000 (46,600 in the U.S.) | Top U.S. locations: San Francisco Bay Area, Boston, Denver | Most notable skills: Oracle Cloud, NetSuite, OCI | Most common job titles: Software Engineer, Business Development Consultant, Application Sales Manager | Largest job functions: Engineering, Sales, Information Technology

See jobs at Oracle

 Salesforce

Salesforce is the parent company of Slack, Mulesoft, Buddy Media, Tableau, and others.

Global headcount: 74,300 (41,000 in the U.S.) | Top U.S. locations: San Francisco Bay Area, Seattle, New York City | Most notable skills: Salesforce.com Administration, Salesforce Sales Cloud, Slack | Most common job titles: Account Executive, Software Engineer, Solutions Engineer | Largest job functions: Sales, Engineering, Information Technology

See jobs at Salesforce

Cisco

Cisco is the parent company of Duo Security and others.

Global headcount: 81,800 (38,800 in the U.S.) | Top U.S. locations: San Francisco Bay Area; Raleigh-Durham, N.C.; Dallas | Most notable skills: Software as a Service (SaaS), Kubernetes, Network Engineering | Most common job titles: Software Engineer, Account Manager, Program Manager | Largest job functions: Engineering, Information Technology, Sales

See jobs at Cisco

Cognizant

Global headcount: 330,600 (34,680 in the U.S.) | Top U.S. locations: New York City, Dallas, Chicago | Most notable skills: Amazon Web Services (AWS), Software Development Life Cycle (SDLC), Agile & Waterfall Methodologies | Most common job titles: Project Manager, Software Engineer, Technical Lead | Largest job functions: Engineering, Information Technology, Program and Project Management

See jobs at Cognizant | See people you may know at Cognizant

Siemens

Siemens is the parent company of Mendix and others.

Global headcount: 303,000 (with 40,000 in the U.S.) | Top U.S. locations: New York City, Philadelphia, Atlanta | Most notable skills: Building Automation, HVAC Controls, Electrical Troubleshooting | Most common job titles: Project Manager, Software Engineer, Senior Sales Executive | Largest job functions: Engineering, Sales, Operations

See jobs at Siemens

Juniper Networks

Global headcount: 10,400 (with 4,400 in the U.S.) | Top U.S. locations: San Francisco Bay Area, Boston, Washington D.C. | Most notable skills: Junos, Kubernetes, Border Gateway Protocol (BGP) | Most common job titles: Software Engineer, System Engineer, Technical Support Engineer  | Largest job functions: Engineering, Sales, Information Technology

See jobs at Juniper Networks

Viasat

Viasat is the parent company of RigNet and others.

Global headcount: 5,800 | Top U.S. locations: San Diego, Denver, Atlanta | Most notable skills: RF Test, Amazon Web Services (AWS), Satellite Communications (SATCOM) | Most common job titles: Software Engineer, Program Manager, System Engineer | Largest job functions: Engineering, Information Technology, Operations

See jobs at Viasat

MathWorks

Global headcount: 5,000 (with 3,000 in the U.S.) | Top U.S. locations: Boston, Detroit, Los Angeles | Most notable skills: MATLAB, Simulink, Deep Learning | Most common job titles: Software Engineer, Application Support Engineer, Principal Software Engineer | Largest job function: Engineering, Information Technology, Sales

See jobs at MathWorks

 

LinkedIn’s Key Trends Of 2022

  • Flexible work is becoming table stakes for recruiting and retaining employees. With job seekers and employees in the driver’s seat and able to ask for the work-life balance they need, flexible work has become required to attract and retain top talent. Most companies on this year’s list offer some form of work-from-anywhere flexibility, with more than 70,000 remote jobs open now across the top 50 companies. Many companies also allow employees to set their schedules and work custom “on” hours through asynchronous work. Some, like Amazon (#1), Raytheon Technologies (#21), and General Motors (#44), are encouraging work-life balance with company-wide days off, while others offer unlimited paid vacation and sabbaticals. In addition, many companies are testing out new flexible offerings – employees at Cisco (#30) have adopted a four-day workweek through the company’s Interim Reduced Workweek program, IBM (#6) has set mandatory “off” hours, Cognizant (#33) offers the option to work a compressed week through its WorkFlex program, Realogy (#40) has a no meetings policy on “Focus Fridays,” Publicis Groupe (#41) allows employees the freedom to work from anywhere they like for up to six weeks per year and PwC (#32) allows employees to step away from work for up to six months while paid through its new Leave of Absence program.
  • Top companies offer stability in an unstable world. While many companies across the U.S. have faced challenges and disruptions over the last year, the Top Companies offer stability and upskilling opportunities that employees can count on – from tuition assistance and PTO for professional development to mentorship programs and job shadowing. Many organizations instituted new programs to retain employees. For example, Deloitte (#11) introduced a new Talent Experience Office focused on employee sentiments and preferences to help inform company choices, EY (#22) offers a Pathway to Purpose virtual program to help employees discover and live their personal purpose and vision, and Kimley-Horn (#31) offers job rotations, so employees learn from different roles and departments. Amazon (#1) is investing $1.2 billion to expand its education and skills training initiatives, Walmart (#5) gives field-based associates access to a no-cost college degree through its Live Better U program, and Verizon (#18) offers an apprenticeship program for those facing employment loss due to automation in technology to prepare them for the jobs of the future. PwC (#32) invested $3 billion in a “New World. New Skills” commitment to equip employees with digital training and awarded a “thank you” bonus of one-week extra pay. Bank of America (#8) provided an additional $1 billion in compensation stock awards to employees globally, and Northrop Grumman (#38) enhanced their annual bonus plan in addition to their ongoing stay interviews.
  • Mental health care is going mainstream across hiring and talent management. To keep employees healthy and happy at work, almost all of this year’s honorees now provide services that address mental health and well-being. Companies like Intel (#23), Salesforce (#28), and Juniper Networks (#46) provide dedicated mental health days, with many – including FedEx (#47) and Blackstone (#43) – offering company-paid mental health benefits. In addition, EY (#22) has expanded its no-cost counseling and mental health coaching sessions to 25 per year for employees and family. Deloitte (#11) provides a $1,000 well-being subsidy in addition to individualized psychological health resources. Unitedhealth Group (#13) provides complimentary access to wellness apps offering coaching, talk therapy, and more.
  • Authenticity, compassion, and curiosity are must-have skills. Most of the Top Companies do not require college degrees and instead look for soft skills that can translate across departments and roles. For example, the #1 skill Comcast (#10) seeks in new hires is authenticity, HCA Healthcare (#37) wants new hires to possess compassion, and Dell Technologies (#14) looks for people who thrive in an environment with a diversity of people and ideas. Accenture (#17), Oracle (#27), and Lockheed Martin (#29) value candidates with curiosity and eagerness to learn and grow. Alphabet (#2) looks for problem-solving skills and a growth mindset.

LinkedIn’s Top 50 Companies In The U.S., 2022

  1. Amazon
  2. Alphabet
  3. Wells Fargo
  4. JPMorgan Chase & Co.
  5. Walmart
  6. IBM
  7. AT&T
  8. Bank of America
  9. Apple
  10. Comcast
  11. Deloitte
  12. Meta
  13. UnitedHealth Group
  14. Dell Technologies
  15. CVS Health
  16. The Walt Disney Company
  17. Accenture
  18. Verizon
  19. GE
  20. Boeing
  21. Raytheon Technologies
  22. EY
  23. Intel
  24. Keller Williams
  25. Kaiser Permanente
  26. Target
  27. Oracle
  28. Salesforce
  29. Lockheed Martin
  30. Cisco
  31. Kimley-Horn
  32. PwC
  33. Cognizant
  34. Citi
  35. Citadel
  36. Johnson & Johnson
  37. HCA Healthcare
  38. Northrop Grumman
  39. Siemens
  40. Realogy
  41. Publicis Groupe
  42. Whiting-Turner
  43. Blackstone
  44. General Motors
  45. Capital One
  46. Juniper Networks
  47. FedEx
  48. Ford Motor Company
  49. Viasat
  50. MathWorks

 

Four Interesting Insights From Gartner 2020 CRM Market Share Update

Four Interesting Insights From Gartner 2020 CRM Market Share Update
  • “The worldwide CRM market grew from $61.6 billion in 2019.  The CRM market grew 12.6% to $69.3 billion in 2020, a strong performance but with wide variations in growth due to pandemic impacts.  However, CRM generally continues to thrive and grow above the overall software industry average rates, which were 8.8% in 2020”.
  • “CRM accounted for the largest share in the overall enterprise software market at 29%”
  • “Salesforce’s  CRM revenue grows by 18.8%, Reaching $13.5 billion In 2020”.
  • “SAP and Oracle each witnessed a slight decrease in market share to 5.2% and 4.4%, respectively, in 2020, down slightly from 5.7% and 4.7% in 2019”.

“The worldwide CRM market grew by 12.6% to $69.3 billion in 2020, up by $7.77 billion from 2019. CRM is the software market  and the third fastest-growing” according to the Gartner, Market Share Analysis: Customer Experience and Relationship Management Software, Worldwide, 2020, by Julian Poulter, Yanna Dharmasthira, Neha Gupta, Amarendra, 16 June 2021.

Gartner found that “Digital commerce grew at a rate of 17.1%, up from 13.2% growth in the prior year, highlighting the shift to digital”. The research firm also defined a new CRM submarket called Cross-CRM comprised of Customer Data Platform (CDP) and Voice of the Customer (VoC) spending. According to Gartner, “Customer Service and Support (CSS) also continues to be the largest segment in the overall CRM market, accounting for 35.5%share. The following graphic compares the top five vendors’ revenue by subsegments:

Four Interesting Insights From Gartner 2020 CRM Market Share Update

Additional interesting insights from Gartner latest CRM market share update include the following:

  • Five vendors comprise 35.6% of an increasingly fragmented CRM market. “Salesforce, SAP, Oracle, Adobe, and Microsoft jointly held share in the CRM market is at 35.6%, up slightly from 35.2% in 2019, while still leaving a highly fragmented 23% stake for 81 named vendors (that we track in market share) and 41.5% stake for the remaining large number of other software vendor”s. “Shopify grew 41.5% year on year, a higher rate than the previous year’s 38%”.
Four Interesting Insights From Gartner 2020 CRM Market Share Update
  • Salesforce, Microsoft, and Adobe grew faster than the market in 2020.  “Salesforce’s CRM revenue grows by 18.8%, Reaching $13.5 Billion in 2020”. Microsoft’s CRM Revenue grew by 17.5% in 2020. Sales is its largest segment with 61% of its CRM revenue and achieved 13.7% growth, above the sales average growth of 10.9% suggesting Dynamics attractive price point, integrated with Power Platform and Office and as a unified CRM suite, are appealing to buyers”. Adobe is the most significant marketing software vendor with its “CRM revenue totaling $2.4 billion in 2020 (just ahead of Salesforce at $2.35 billion), up from $2.1 billion in 2019”.
Four Interesting Insights From Gartner 2020 CRM Market Share Update
  • $55 billion of 2020 CRM sales were cloud-based, comprising 79.4% of all sales, increasing from $47.7 billion in 2019. Gartner believes that “Cloud growth was slightly slower due to the pandemic, and on-premises software (new license and software support services) still had very small growth of just over 4% up from the previous year”. Vertical market niche-based applications are sold on-premise, including those tailored to the specific needs of banking, financial services, manufacturing, and process industries’ operations.
  • “North America and Western Europe hold the largest share in the CRM market, with 59.6% and 20.7% stakes, respectively”. According to Gartner, “Mature APAC and Japan emerged as the fastest-growing regions with 19.2% and 17.5% growth rates respectively. Adoption lags in these markets compared with North America and Western Europe, and this higher growth rate shows more investment as companies catch up. At the moment however, Mature APAC and Japan together only account for about 9% of the overall CRM market share”.
  • Global spending on Customer Service and Support (CSS) grew 12.9% in 2020, down from 14.78% in 2019.   “The CSS market saw growth of 12.9% in 2020, down from 14.78% in 2019, reaching $24.6 billion, up from $21.8 billion in 2019”. “The leading vendor in the CSS segment is Salesforce , with $5.3 billion in revenue,with service being its biggest cloud, overtaking sales in 2020”, according to Gartner. The next three top vendors include Genesys, Oracle and Zendesk – with Zendesk replacing SAP at No. 4 Zendesk,  achieved revenue of $866 million and a growth rate of 25.1%”.

Source:

Gartner, ‘Market Share Analysis: Customer Experience and Relationship Management Software, Worldwide, 2020’, Julian Poulter, Yanna Dharmasthira, Neha Gupta, Amarendra, June 16, 2021 (client access required)

LinkedIn Best Companies To Work For In 2021 Dominated By Tech

  • Four of LinkedIn’s top ten companies to grow your career in 2021 are tech leaders.
  • Amazon is the highest rated company, followed by Alphabet (2nd), IBM (6th), and Apple (8th).
  • 15 of the 50 top companies in the U.S. are in the tech industry, including Oracle, Salesforce, and SAP.

These and many other insights are from the LinkedIn Top Companies 2021: The 50 best workplaces to grow your career in the U.S. published today. All 50 companies are currently hiring and have over 300,000 jobs available right now. LinkedIn’s analysis of the best companies to grow your career spans 20 countries, including Australia, BrazilCanadaChinaFranceGermanyIndiaItalyJapanMalaysiaMexico, the Netherlands, the PhilippinesSaudi ArabiaSingaporeSpainQatar, the UAE, and the U.K. 

LinkedIn is relying on a new methodology for the 2021 Top Companies Report. They’re basing the methodology has seven key pillars, each revealing an important element of career progression: the ability to advance, skills growth, company stability, external opportunity, company affinity, gender diversity, and educational background. LinkedIn provides an in-depth description of how they built their methodology here.

The 10 Best Companies To Grow Your Career In 2021

  1. Amazon – According to LinkedIn, Amazon has built an innovative remote-onboarding system, and it has more than 30,000 openings now. The fastest-growing skills in demand at Amazon include User Experience Design (UED), Digital Illustration, and Interaction Design. LinkedIn’s analysis shows the most in-demand jobs are Health And Safety Specialist, Station Operations Manager, Learning Manager.
  1. Alphabet, Inc – Planning to add at least 10,000 jobs in the U.S. alone and investing $7B in data centers and offices across 19 states, Alphabet grew revenue 47% last year, reaching $13B.  According to LinkedIn, the most in-demand jobs are Digital Specialist, Field Sales Specialist, and Business Systems Analyst.
  1. JPMorgan Chase & Co. – JPMorgan now offers 300 accredited skills and education programs to its workers, and the bank has been boosting wages for thousands of customer-facing roles to $16-$20 an hour. The most in-demand jobs include Market Specialist, Software Engineering Specialist, and Mortgage Underwriter.
  1. AT&T – 2020 was a tough year for AT&T, increasing the urgency the company has to grow its wireless and WarnerMedia businesses. Due to the pandemic, the company had to close hundreds of stores. Fortunately, AT&T was able to help the employees affected by the closures to find new jobs. The most in-demand jobs are Service Analyst, Trading Analyst, and Investment Specialist.
  1. Bank of America – Bank of America rose to the challenges of 2020, quickly redeploying almost 30,000 employees to assist in its role facilitating the government-backed Paycheck Protection Program. The most in-demand jobs are Trading Analyst, Investment Specialist, and Financial Management Analyst.
  1. IBM – More than one-third of IBM’s revenue now comes from work related to cloud computing. The company’s Red Hat unit is a leading contributor to that growth, prizing skills such as Linux, Java, Python, and agile methodologies. IBM also is a leader in hiring autistic people through its Neurodiversity program. Most in-demand jobs include Back End Developer, Enterprise Account Executive, and Technical Writer.
  1. Deloitte –  Deloitte’s key activities span audit, assurance, tax, risk, and financial advisory work, as well as management consulting. It’s aiming to hire 19,000 people in the year ending May 29. Top recruiting priorities currently include cybersecurity, cloud computing, and analytics specialists.
  1. Apple – LinkedIn finds that Apple is committed to building an inclusive culture. Over half of its new hires in the U.S. represent historically underrepresented groups in tech — and the company claims to have achieved pay equity in every country where it operates—looking for an in? Apple has nearly 3,000 open jobs in the U.S. right now, ranging from its “genius” role at its retail stores to executive assistants and software engineers. 
  1. Walmart –  In February, the retail giant promised further raises to over 400,000 of its people and months later announced it would increase the share of its hourly store employees who work full-time to over 66% (up from 53% five years ago). Meanwhile, Walmart continues to think beyond the store as it ventures deeper into the e-commerce realm. Most in-demand jobs include Operational Specialist, Fulfillment Associate, and Replenishment Manager.
  1. EY – The accounting firm spent $450 million on employee training in 2020. And it is planning to hire over 15,000 people in the next year. With that much talent coming in, EY is focused on bringing in workers with diverse backgrounds, focusing on gender identity, race, and ethnicity, disability, LGBT+, and veterans. The most in-demand jobs include Strategy Director, Business Transformation Consultant, and Information Technology Consulting Manager.

FinancialForce’s Spring 2021 Release Shows Why Being Customer-Centric Pays

FinancialForce's Spring 2021 Release Shows Why Being Customer-Centric Pays

Bottom Line: Customer revenue lifecycles are the lifeblood of any services business, making FinancialForce’s Spring 2021 release timely given the services-first revenue renaissance happening today.

The essence of an excellent services business is that it can consistently create expectations clients trust and the business regularly exceeds. Orchestrating the best people for a given project at the right time, tracking costs, revenue, and margin across all services revenue, including those associated with a client’s assets, is very challenging. Customer revenue lifecycles are in the data, yet no one can get to them because they’re hidden across multiple systems that aren’t integrated. Knowing how efficient a services business is at turning customer engagement into cash is what everyone needs to know, but no one can find. The challenge is equally as daunting for long-established services providers and those rushing into new services businesses to redefine themselves in the hope of profits that are more consistent and fewer price wars.

How Much Is Customer Engagement Is Worth?

Services businesses face the paradox of exceeding client expectations with every engagement but not knowing if extra time, resources, and staff invested are paying off with more revenue and profit. FinancialForce’s Spring 2021 release looks to solve this problem. What galvanizes the ERP, PSA, and platform announcements is a fresh intensity on customer centricity, both for the services business adopting the Spring 2021 release and the customers it’s intended to serve.

Knowing if and by how much a given customer engagement and its revenue lifecycle generate cash, and its potential is one of the core focus areas of the Spring 2021 release. It’s badly needed as many services are flying blind today, overcommitting resources for little return and too often losing control of client engagement and paying the price in lost margin and profits. FinancialForce sees that pain and wants to alleviate it with better financial visibility on all aspects of customer services revenue. FinancialForce aims to provide customer-centric financial reporting down to the revenue stream and costing measure level.  

FinancialForce's Spring 2021 Release Shows Why Being Customer-Centric Pays
Knowing every customer’s impact on revenue and profitability from all revenue streams will make managing services engagements much more accurate, easier to manage, and more profitable. 

Key Takeaways From The Spring 2021 Release

Customer centricity seen through a financial lens is the cornerstone of FinancialForce’s latest release. One of the primary goals of this release is to update more applications to Salesforce Lightning to provide FinancialForce users with a more consistent user experience across all applications.  Salesforce has been doubling down for years on Lightning and its user experience technologies, with FinancialForce reaping the benefits for over a decade. FinancialForce is transitioning their core Professional Services Automation (PSA), Billing, Accounting & Finance and Procurement, Order and Inventory Management to Lightning in this release in response to their customers wanting a consistent user experience across the entire FinancialForce suite of applications.  The Spring 2021 release reflects how FinancialForce strives to provide a real-time understanding of customer lifetime value for their ERP and PSA customers.  

Additional key takeaways include the following:

  • FinancialForce sees reducing days to close as one of the highest priorities they need to address today. The majority of new feature announcements center on how the days to close cycles can be streamlined, especially across multi-company and multisite locations across geographic and currency-specific regions of the world. Multi-company currency revaluation will help FinancialForce customers who operate across multiple geographies that operate in different currencies and will be especially useful for those clients creating new global channels and considering foreign acquisitions. Further showing the high priority they are putting on reducing days to close, the Spring 2021 release also includes automated eliminations, multi-company period close for software closes, which are designed to temporarily close out a financial report and revenue schedules that can provide a future view in revenues – a key factor in knowing customer revenue lifecycles.
  • New features and a new Lightning interface for Accounting, Billing Central, and Inventory Management simplifies complex transactions for users. FinancialForce has one of the most customer-driven product management teams in enterprise software. The depth of features they have added to inventory management, transactional and reconciliation processes for accounting, drop-ship use cases, and enhancements for adding products to billing contracts show how much FinancialForce is listening to customers.
  • AI-enhanced financial reporting that works with any Einstein data set. FinancialForce leads the Salesforce partner ecosystem when it comes to integrating Tableau CRM (formerly known as Einstein Analytics) into its platform. Now thirteen releases in, FinancialForce’s Spring 2021 release reflects the intuitive, adaptive intelligence that the product management team aims to achieve by integrating Einstein into their financial reporting workflows. 
  • Professional Services Automation (PSA) Applications Including Resource Management, Project Management, and Time & Expense upgraded to Lightning.  Transitioning three of the core PSA applications to Lightning will help broaden adoption and make them easier to upsell and cross-sell across the FinancialForce customer base. It will also help existing customers using these applications get new employees up to speed faster on them, given how much more streamlined Lightning is as an interface compared to previous versions.
  • Intelligent Staffing solves the complex challenges resource managers face when assigning the best possible associates to a given project. Designed to filter and intelligently rank potential resources based on region, practice, group skill sets, and availability, Intelligent Staffing is designed to get resource managers as close to an ideal match as possible for a given project’s requirements. This is a much-welcomed new feature by FinancialForce customers who are large-scale services providers as they’re facing the challenges of assigning the right person to the right project at the right time to ensure project success.    
  • Integration of Salesforce AI’s Next Best Action (NBA) will raise the level of project expertise at scale across customers.  Part of the customer centricity focus in Spring 2021 is focused on providing customers with new technologies and applications to share expertise and knowledge at scale. Next Best Action provides prescriptive guidance for the project manager and will see heavy use in new associate onboarding across services businesses and achieve greater corporate-wide learning at scale. This is consistent with the focus in the Spring 2021 release on bringing greater space and speed to mid-size and larger services customers.

Conclusion

FinancialForce defines customer engagement and centricity from a financial standpoint in the Spring 2021 release. Too often, services businesses commit to large-scale projects without a clear idea of the customer revenue lifecycle. With FinancialForce, they can stop and ask if the level of customer engagement they’re committing to is worth it or not – and if it isn’t, what needs to be done. FinancialForce is doubling down on user experience and accelerating time-to-close, two areas their customers want innovation to and look to them to deliver. Look for FinancialForce to scale out with more MuleSoft and Tableau integration scenarios, all aimed at capitalizing on their expertise developing on the Salesforce platform. There’s a bigger challenge to customer engagement on the horizon, and that’s providing a real-time view of financials across all customers with all available data across a business, making MuleSoft integration key to FinancialForce’s future growth.

COVID-19’s Impact On Tech Spending This Year

COVID-19's Impact On Tech Spending This Year

The human tragedy the COVID-19 pandemic has inflicted on the world is incalculable and continues to grow. Every human life is priceless and deserves the care needed to sustain it. COVID-19 is also impacting entire industries, causing them to randomly gyrate in unpredictable ways, directly impacting IT and tech spending.

COVID-19’s Impact On Industries

Computer Economics in collaboration with their parent company Avasant published their Coronavirus Impact Index by Industry that looks at how COVID-19 is affecting 11 major industry sectors in four dimensions: personnel, operations, supply chain, and revenue. Please see the Coronavirus Impact Index by Industry by Tom Dunlap, Dave Wagner, and Frank Scavo of Computer Economics for additional information and analysis.  The resulting index is an overall rating of the impact of the pandemic on each industry and is shown below:

Computer Economics and Avasant predict major disruption to High Tech & Telecommunications based on the industry’s heavy reliance on Chinese supply chains, which were severely impacted by COVID-19. Based on conversations with U.S.-based high tech manufacturers, I’ve learned that a few are struggling to make deliveries to leading department stores and discount chains due to parts shortages and allocations from their Chinese suppliers. North American electronics suppliers aren’t an option due to their prices being higher than their Chinese competitors. Leading department stores and discount chains openly encourage high tech device manufacturers to compete with each other on supplier availability and delivery date performance.

In contrast to the parts shortage and unpredictability of supply chains dragging down the industry, software is a growth catalyst. The study notes that Zoom, Slack, GoToMyPC, Zoho Remotely, Microsoft Office365, Atlassian, and others are already seeing increased demand as companies increase their remote-working capabilities.

COVID-19’s Impact On IT Spending  

Further supporting the Coronavirus Impact Index by Industry analysis, Andrew Bartels, VP & Principal Analyst at Forrester, published his latest forecast of tech growth today in the post, The Odds of a Tech Market Decline In 2020 Have Just Gone Up To 50%.

Mr. Bartels is referencing the market forecasts shown in the following forecast published last month, New Forrester Forecast Shows That Global Tech Market Growth Will Slip To 3% In 2020 And 2021 and shown below:

Key insights from Forrester’s latest IT spending forecast and predictions are shown below:

  • Forrester is revising its tech forecast downward, predicting the US and global tech market growth slowing to around 2% in 2020. Mr. Bartels mentions that this assumes the US and other major economies have declined in the first half of 2020 but manage to recover in the second half.
  • If a full-fledged recession hits, there is a 50% probability that US and global tech markets will decline by 2% or more in 2020.
  • In either a second-half 2020 recovery or recession, Forrester predicts computer and communications equipment spending will be weakest, with potential declines of 5% to 10%.
  • Tech consulting and systems integration services spending will be flat in a temporary slowdown and could be down by up to 5% if firms cut back on new tech projects.
  • Software spending growth will slow to the 2% to 4% range in the best case and will post no growth in the worst case of a recession.
  • The only positive signs from the latest Forrester IT spending forecast is the continued growth in demand for cloud infrastructure services and potential increases in spending on specialized software. Forrester also predicts communications equipment, and telecom services for remote work and education as organizations encourage workers to work from home and schools move to online courses.

Conclusion

Every industry is economically hurting already from the COVID-19 pandemic. Now is the time for enterprise software providers to go the extra mile for their customers across all industries and help them recover and grow again. Strengthening customers in their time of need by freely providing remote collaboration tools, secure endpoint solutions, cloud-based storage, and CRM systems is an investment in the community that every software company needs to make it through this pandemic too.

Salesforce Now Has Over 19% Of The CRM Market

 

  • Salesforce dominated the worldwide CRM market with a 19.5% market share in 2018, over double its nearest rival, SAP, at 8.3% share.
  • Worldwide spending on customer experience and relationship management (CRM) software grew 15.6% to reach $48.2B in 2018.
  • 72.9% of CRM spending was on software as a service (SaaS) in 2018, which is expected to grow to 75% of total CRM software spending in 2019.
  • Worldwide enterprise application software revenue totaled more than $193.6B in 2018, a 12.5% increase from 2017 revenue of $172.1B. CRM made up nearly 25% of the entire enterprise software revenue market.

CRM remains the largest and fastest growing enterprise software category today according to the latest market sizing, and market share research Gartner published this weekGartner defines CRM as providing the functionality to companies across the four segments of customer service and support, digital commerce, marketing, and sales. All four subsegments of the CRM market grew by more than 13.7%, with marketing emerging as the fastest growing segment, increasing by 18.8% and representing more than 25% of the entire CRM market. Customer service and support retain its No. 1 position, contributing 35.7% of CRM market revenue, attaining $17.1B in revenues in 2018.

Key insights include the following:

  • With 19.5% market share, Salesforce has over 2X the CRM sales SAP has and over 3X of Oracle. Salesforce continues to dominate CRM globally, increasing its market share from 18.3% in 2017 to 19.5% in 2018. Adobe is the only other vendor to grow its market share in 2018. Microsoft and SAP successfully held onto to market share while Oracle lost share.

  • Adobe and Salesforce grew faster than the overall market, increasing CRM revenues 21.7% and 23.2% respectively. Adobe’s CRM sales jumped from $2B in 2017 to $2.4B in 2018. Salesforce CRM revenues increased from $7.6B in 2017 to $9.4B in 2018, growing the fastest of all competitors in this market. SAP grew 15.5% between 2017 and 2018, just below the overall market growth of 15.6%. Microsoft (15%) and Oracle (7.1%) grew slower than the market. The following graphic compares growth rates between 2017 and 2018.

  • Adobe dominates the marketing subsegment of CRM with 19% market share in 2018. Salesforce has 11.7% of the marketing subsegment, followed by IBM (5.7%), SAP (4%), Oracle (3.6%) and HubSpot (3.4%). Gartner estimates the marketing subsegment was a $12.2B market in 2018, increasing from $10.3B in 2017, achieving 18.8% growth in just a year.
  • Eastern and Western Europe were the fastest growing regions at 19.7% and 17.5% respectively. North America and Western Europe were the largest two regions with North America growing at 15.2% to reach $28.1B in revenue.

Sources:

Gartner Says Worldwide Customer Experience and Relationship Management Software Market Grew 15.6% in 2018

Market Share: Customer Experience and Relationship Management, Worldwide, 2018 (client access required)

10 Ways Machine Learning Is Revolutionizing Sales

  • Sales teams adopting AI are seeing an increase in leads and appointments of more than 50%, cost reductions of 40%–60%, and call time reductions of 60%–70% according to the Harvard Business Review article Why Salespeople Need to Develop Machine Intelligence.
  • 62% of highest performing salespeople predict guided selling adoption will accelerate based on its ability rank potential opportunities by value and suggest next steps according to Salesforces’ latest State of Sales research study.
  • By 2020, 30% of all B2B companies will employ AI to augment at least one of their primary sales processes according to Gartner.
  • High-performing sales teams are 4.1X more likely to use AI and machine learning applications than their peers according to the State of Sales published by Salesforce.
  • Intelligent forecasting, opportunity insights, and lead prioritization are the top three AI and machine learning use cases in sales.

Artificial Intelligence (AI) and machine learning show the potential to reduce the most time-consuming, manual tasks that keep sales teams away from spending more time with customers. Automating account-based marketing support with predictive analytics and supporting account-centered research, forecasting, reporting, and recommending which customers to upsell first are all techniques freeing sales teams from manually intensive tasks.

The Race for Sales-Focused AI & Machine Learning Patents Is On

CRM and Configure, Price & Quote (CPQ) providers continue to develop and fine-tune their digital assistants, which are specifically designed to help the sales team get the most value from AI and machine learning. Salesforces’ Einstein supports voice-activation commands from Amazon Alexa, Apple Siri, and Google. Salesforce and other enterprise software companies continue aggressively invest in Research & Development (R&D). For the nine months ended October 31, 2018, Salesforce spent $1.3B or 14% of total revenues compared to $1.1B or 15% of total revenues, during the same period a year ago, an increase of $211M according to the company’s 10Q filed with the Securities and Exchange Commission.

The race for AI and machine learning patents that streamline selling is getting more competitive every month. Expect to see the race of sales-focused AI and machine learning patents flourish in 2019. The National Bureau of Economic Research published a study last July from the Stanford Institute For Economic Policy Research titled Some Facts On High Tech Patenting. The study finds that patenting in machine learning has seen exponential growth since 2010 and Microsoft had the greatest number of patents in the 2000 to 2015 timeframe. Using patent analytics from PatentSight and ipsearchIAM published an analysis last month showing Microsoft as the global leader in machine learning patents with 2,075.  The study relied on PatentSight’s Patent Asset Index to rank machine learning patent creators and owners, revealing Microsoft and Alphabet are dominating today. Salesforce investing over $1B a year in R&D reflects how competitive the race for patents and intellectual property is.

10 Ways Machine Learning Is Revolutionizing Sales

Fueled by the proliferation of patents and the integration of AI and machine learning code into CRM, CPQ, Customer Service, Predictive Analytics and a wide variety of Sales Enablement applications, use cases are flourishing today. Presented below are the ten ways machine learning is most revolutionizing selling today:

 

  1. AI and machine learning technologies excel at pattern recognition, enabling sales teams to find the highest potential new prospects by matching data profiles with their most valuable customers. Nearly all AI-enabled CRM applications are providing the ability to define a series of attributes, characteristics and their specific values that pinpoint the highest potential prospects. Selecting and prioritizing new prospects using this approach saves sales teams thousands of hours a year.
  2. Lead scoring and nurturing based on AI and machine learning algorithms help guide sales and marketing teams to turn Marketing Qualified Leads (MQL) into Sales Qualified Leads (SQL), strengthening sales pipelines in the process. One of the most important areas of collaboration between sales and marketing is lead nurturing strategies that move prospects through the pipeline. AI and machine learning are enriching the collaboration with insights from third-party data, prospect’s activity at events and on the website, and from previous conversations with salespeople. Lead scoring and nurturing relies heavily on natural language generation (NLG) and natural-language processing (NLP) to help improve each lead’s score.
  3. Combining historical selling, pricing and buying data in a single machine learning model improves the accuracy and scale of sales forecasts. Factoring in differences inherent in every account given their previous history and product and service purchasing cycles is invaluable in accurately predicting their future buying levels. AI and machine learning algorithms integrated into CRM, sales management and sales planning applications can explain variations in forecasts, provided they have the data available. Forecasting demand for new products and services is an area where AI and machine learning are reducing the risk of investing in entirely new selling strategies for new products.
  4. Knowing the propensity of a given customer to churn versus renew is invaluable in improving Customer Lifetime Value. Analyzing a diverse series of factors to see which customers are going to churn or leave versus those that will renew is among the most valuable insights AI and machine learning is delivering today. Being able to complete a Customer Lifetime Value Analysis for every customer a company has provides a prioritized roadmap of where the health of client relationships are excellent versus those that need attention. Many companies are using Customer Lifetime Value Analysis as a proxy for a customer health score that gets reviewed monthly.
  5. Knowing the strategies, techniques and time management approaches the top 10% of salespeople to rely on to excel far beyond quota and scaling those practices across the sales team based on AI-driven insights. All sales managers and leaders think about this often, especially in sales teams where performance levels vary widely. Knowing the capabilities of the highest-achieving salespeople, then selectively recruiting those sales team candidates who have comparable capabilities delivers solid results. Leaders in the field of applying AI to talent management include Eightfold whose approach to talent management is refining recruiting and every phase of managing an employee’s potential. Please see the recent New York Times feature of them here.
  6. Guided Selling is progressing rapidly from a personalization-driven selling strategy to one that capitalized on data-driven insights, further revolutionizing sales. AI- and machine learning-based guided selling is based on prescriptive analytics that provides recommendations to salespeople of which products, services, and bundles to offer at which price. 62% of highest performing salespeople predict guided selling adoption will accelerate based on its ability rank potential opportunities by value and suggest next steps according to Salesforces’ latest State of Sales research study.
  7. Improving the sales team’s productivity by using AI and machine learning to analyze the most effective actions and behaviors that lead to more closed sales. AI and machine learning-based sales contact and customer predictive analytics take into account all sources of contacts with customers and determine which are the most effective. Knowing which actions and behaviors are correlated with the highest close rates, sales managers can use these insights to scale their sales teams to higher performance.
  8. Sales and marketing are better able to define a price optimization strategy using all available data analyzing using AI and machine learning algorithms. Pricing continues to be an area the majority of sales and marketing teams learn to do through trial and error. Being able to analyze pricing data, purchasing history, discounts are taken, promotional programs participated in and many other factors, AI and machine learning can calculate the price elasticity for a given customer, making an optimized price more achievable.
  9. Personalizing sales and marketing content that moves prospects from MQLs to SQLs is continually improving thanks to AI and machine learning. Marketing Automation applications including HubSpot and many others have for years been able to define which content asset needs to be presented to a given prospect at a given time. What’s changed is the interactive, personalized nature of the content itself. Combining analytics, personalization and machine learning, marketing automation applications are now able to tailor content and assets that move opportunities forward.
  10. Solving the many challenges of sales engineering scheduling, sales enablement support and dedicating the greatest amount of time to the most high-value accounts is getting solved with machine learning. CRM applications including Salesforce can define a salesperson’s schedule based on the value of the potential sale combined with the strength of the sales lead, based on its lead score. AI and machine learning optimize a salesperson’s time so they can go from one customer meeting to the next, dedicating their time to the most valuable prospects.

The Best Big Data Companies And CEOs To Work For In 2018

Forbes readers’ most common requests center on who the best companies are to work for in analytics, big data, data management, data science and machine learning. The latest Computer Reseller News‘ 2018 Big Data 100 list of companies is used to complete the analysis as it is an impartial, independent list aggregated based on CRN’s analysis and perspectives of the market. Using the CRN list as a foundation, the following analysis captures the best companies in their respective areas today.

Using the 2018 Big Data 100 CRN list as a baseline to compare the Glassdoor scores of the (%) of employees who would recommend this company to a friend and (%) of employees who approve of the CEO, the following analysis was completed today. 25 companies on the list have very few (less than 15) or no Glassdoor reviews, so they are excluded from the rankings. Based on analysis of Glassdoor score patterns over the last four years, the lower the number of rankings, the more 100% scores for referrals and CEOs. These companies, however, are included in the full data set available here. If the image below is not visible in your browser, you can view the rankings here.

 

The highest rated CEOs on Glassdoor as of May 11, 2018 include the following:

Dataiku Florian Douetteau 100%
StreamSets Girish Pancha 100%
MemSQL Nikita Shamgunov 100%
1010 Data Greg Munves 99%
Salesforce.com Marc Benioff 98%
Attivio Stephen Baker 98%
SAP Bill McDermott 97%
Qubole Ashish Thusoo 97%
Trifacta Adam Wilson 97%
Zaloni Ben Sharma 97%
Reltio Manish Sood 96%
Microsoft Satya Nadella 96%
Cloudera Thomas J. Reilly 96%
Sumo Logic Ramin Sayar 96%
Google Sundar Pichai 95%
Looker Frank Bien 93%
MongoDB Dev Ittycheria 92%
Snowflake Computing Bob Muglia 92%
Talend Mike Tuchen 92%
Databricks Ali Ghodsi 90%
Informatica Anil Chakravarthy 90%

 

10 Ways Machine Learning Is Revolutionizing Manufacturing

machine learningBottom line: Every manufacturer has the potential to integrate machine learning into their operations and become more competitive by gaining predictive insights into production.

Machine learning’s core technologies align well with the complex problems manufacturers face daily. From striving to keep supply chains operating efficiently to producing customized, built- to-order products on time, machine learning algorithms have the potential to bring greater predictive accuracy to every phase of production. Many of the algorithms being developed are iterative, designed to learn continually and seek optimized outcomes. These algorithms iterate in milliseconds, enabling manufacturers to seek optimized outcomes in minutes versus months.

The ten ways machine learning is revolutionizing manufacturing include the following:

  • Increasing production capacity up to 20% while lowering material consumption rates by 4%. Smart manufacturing systems designed to capitalize on predictive data analytics and machine learning have the potential to improve yield rates at the machine, production cell, and plant levels. The following graphic from General Electric and cited in a National Institute of Standards (NIST) provides a summary of benefits that are being gained using predictive analytics and machine learning in manufacturing today.

typical production improvemensSource: Focus Group: Big Data Analytics for Smart Manufacturing Systems

  • Providing more relevant data so finance, operations, and supply chain teams can better manage factory and demand-side constraints. In many manufacturing companies, IT systems aren’t integrated, which makes it difficult for cross-functional teams to accomplish shared goals. Machine learning has the potential to bring an entirely new level of insight and intelligence into these teams, making their goals of optimizing production workflows, inventory, Work In Process (WIP), and value chain decisions possible.

factory and demand analytics

Source:  GE Global Research Stifel 2015 Industrials Conference

  • Improving preventative maintenance and Maintenance, Repair and Overhaul (MRO) performance with greater predictive accuracy to the component and part-level. Integrating machine learning databases, apps, and algorithms into cloud platforms are becoming pervasive, as evidenced by announcements from Amazon, Google, and Microsoft. The following graphic illustrates how machine learning is integrated into the Azure platform. Microsoft is enabling Krones to attain their Industrie 4.0 objectives by automating aspects of their manufacturing operations on Microsoft Azure.

Azure IOT Services

Source: Enabling Manufacturing Transformation in a Connected World John Shewchuk Technical Fellow DX, Microsoft

  • Enabling condition monitoring processes that provide manufacturers with the scale to manage Overall Equipment Effectiveness (OEE) at the plant level increasing OEE performance from 65% to 85%. An automotive OEM partnered with Tata Consultancy Services to improve their production processes that had seen Overall Equipment Effectiveness (OEE) of the press line reach a low of 65 percent, with the breakdown time ranging from 17-20 percent.  By integrating sensor data on 15 operating parameters (such as oil pressure, oil temperature, oil viscosity, oil leakage, and air pressure) collected from the equipment every 15 seconds for 12 months. The components of the solution are shown

OEE Graphic

Source: Using Big Data for Machine Learning Analytics in Manufacturing

  • Machine learning is revolutionizing relationship intelligence and Salesforce is quickly emerging as the leader. The series of acquisitions Salesforce is making positions them to be the global leader in machine learning and artificial intelligence (AI). The following table from the Cowen and Company research note, Salesforce: Initiating At Outperform; Growth Engine Is Well Greased published June 23, 2016, summarizes Salesforce’s series of machine learning and AI acquisitions, followed by an analysis of new product releases and estimated revenue contributions. Salesforce’s recent acquisition of e-commerce provider Demandware for $2.8B is analyzed by Alex Konrad is his recent post,     Salesforce Will Acquire Demandware For $2.8 Billion In Move Into Digital Commerce. Cowen & Company predicts Commerce Cloud will contribute $325M in revenue by FY18, with Demandware sales being a significant contributor.

Salesforce AI Acquisitions

Salesforce revenue sources

  • Revolutionizing product and service quality with machine learning algorithms that determine which factors most and least impact quality company-wide. Manufacturers often are challenged with making product and service quality to the workflow level a core part of their companies. Often quality is isolated. Machine learning is revolutionizing product and service quality by determining which internal processes, workflows, and factors contribute most and least to quality objectives being met. Using machine learning manufacturers will be able to attain much greater manufacturing intelligence by predicting how their quality and sourcing decisions contribute to greater Six Sigma performance within the Define, Measure, Analyze, Improve, and Control (DMAIC) framework.
  • Increasing production yields by the optimizing of team, machine, supplier and customer requirements are already happening with machine learning. Machine learning is making a difference on the shop floor daily in aerospace & defense, discrete, industrial and high-tech manufacturers today. Manufacturers are turning to more complex, customized products to use more of their production capacity, and machine learning help to optimize the best possible selection of machines, trained staffs, and suppliers.
  • The vision of Manufacturing-as-a-Service will become a reality thanks to machine learning enabling subscription models for production services. Manufacturers whose production processes are designed to support rapid, highly customized production runs are well positioning to launch new businesses that provide a subscription rate for services and scale globally. Consumer Packaged Goods (CPG), electronics providers and retailers whose manufacturing costs have skyrocketed will have the potential to subscribe to a manufacturing service and invest more in branding, marketing, and selling.
  • Machine learning is ideally suited for optimizing supply chains and creating greater economies of scale.  For many complex manufacturers, over 70% of their products are sourced from suppliers that are making trade-offs of which buyer they will fulfill orders for first. Using machine learning, buyers and suppliers could collaborate more effectively and reduce stock-outs, improve forecast accuracy and met or beat more customer delivery dates.
  • Knowing the right price to charge a given customer at the right time to get the most margin and closed sale will be commonplace with machine learning.   Machine learning is extending what enterprise-level price optimization apps provide today.  One of the most significant differences is going to be just how optimizing pricing along with suggested strategies to close deals accelerate sales cycles.

Additional reading:

Cisco Blog: Deus Ex Machina: Machine Learning Acts to Create New Business Outcomes

Enabling Manufacturing Transformation in a Connected World John Shewchuk Technical Fellow DX, Microsoft 

Focus Group: Big Data Analytics for Smart Manufacturing Systems

GE Predix: The Industrial Internet Platform

IDC Manufacturing Insights reprint courtesy of Cisco: Designing and Implementing the Factory of the Future at Mahindra Vehicle Manufacturers

Machine Learning: What It Is And Why It Matters

McKinsey & Company, An Executive’s Guide to Machine Learning

MIT Sloan Management Review, Sales Gets a Machine-Learning Makeover

Stanford University CS 229 Machine Learning Course Materials
The Economist Feature On Machine Learning

UC Berkeley CS 194-10, Fall 2011: Introduction to Machine Learning
Lecture slides, notes

University of Washington CSE 446 – Machine Learning – Winter 2014

Sources:

Lee, J. H., & Ha, S. H. (2009). Recognizing yield patterns through hybrid applications of machine learning techniques. Information Sciences, 179(6), 844-850.

Mackenzie, A. (2015). The production of prediction: What does machine learning want?. European Journal of Cultural Studies, 18(4-5), 429-445.

Pham, D. T., & Afify, A. A. (2005, July). Applications of machine learning in manufacturing. In Intelligent Production Machines and Systems, 1st I* PROMS Virtual International Conference (pp. 225-230).

Priore, P., de la Fuente, D., Puente, J., & Parreño, J. (2006). A comparison of machine-learning algorithms for dynamic scheduling of flexible manufacturing systems. Engineering Applications of Artificial Intelligence, 19(3), 247-255.

Salesforce On The State Of Analytics, 2015

  • analytics predictions 2015Between 2015 and 2020, the number of data sources analyzed by enterprises will jump 83%.
  • 9 out of 10 enterprise leaders believe analytics is absolutely essential or very important to their overall business strategies and operational outcomes.
  • 54% of marketers say marketing analytics is absolutely critical or very important to creating a cohesive customer journey.
  • High performing enterprises are 5.4x more likely than underperformers to primarily use analytics tools to gain strategic insights from Big Data.

These and many other interesting insights are from the 2015 State of Analytics study from Salesforce Research. Salesforce conducted the study in mid-2015, generating 2,091 responses from business leaders from enterprises (not limited to Salesforce customers). Geographies included in the study include the U.S., Canada, Brazil, U.K., France, Germany, Japan, and Australia.  While Salesforce is a leading provider of analytics, the report strives to deliver useful insights beyond just endorsing their product direction.

10 insights and predictions on the state of analytics include the following:

  • Between 2015 and 2020, the number of data sources analyzed will jump 83%. Salesforce Research found that the number of data sources actively analyzed by businesses has grown just 20% in the last five years. This is projected to accelerate rapidly, attaining a compound annual growth rate of 120% in the 10-year forecast period. High performing enterprises will be relying on a projected 50 different data sources by 2020, leading all performance categories tracked in the study.

data explosion

  • Relying on manual processes to get all the data in one view (53%) is one of the greatest challenges enterprises face today. Additional factors driving enterprises to integrate more data sources into their analytics applications include finding that too much data is left unanalyzed (53%), spending too much time updating spreadsheets (52%), and analysis is performance by business analysts, not end users of the data (50%).  All of these factors and those shown in the graphic below form the catalyst that is driving greater legacy, 3rd party and broader enterprise data integration into analytics applications.

lack of automation

  • 9 out of 10 enterprise leaders believe analytics is absolutely essential or very important to their overall business strategies and operational outcomes. In addition, 84% of high performers are projecting that the importance of analytics will increase substantially or somewhat in the next two years. 65% of all business leaders surveyed are predicting that the importance of analytics will increase substantially or somewhat in the next two years.

analytics is critical to driving business strategy

  • High performing enterprises are 4.6x more likely than underperformers to agree that data is driving their business decisions. In addition, 60% of high performing enterprises’ leaders agree with the statement that their organizations have moved beyond numbers keeping score to data driving business decisions. Salesforce Research also found that 43% of high performers rely on empirical data, developing hypotheses and then experimenting and observing the outcomes before making a decision.

data drives decisions

  • Driving operational efficiencies and facilitating growth (both 37%) are the two areas enterprises are initially focused on with analytics today.  Once analytics apps are delivering insights and are part of daily workflows, enterprises expand their use into optimizing operational processes (35%), identifying new revenue streams (33%) and predicting customer behavior (32%). The following graphic provides a comparison of the top ten use cases.

analytics every corner

  • High performance enterprises consistently analyze more than 17 different kinds of data across their analytics apps.  In contrast, underperforming organizations only analyze 10 different data sources, and moderate performers, 15. The following graphic provides an overview of the top ten most-used sources of data.

companies track a wide variety of data

  • High performers are 3.5x more likely than underperformers to extensively use mobile reporting tools to analyze data wherever they are. 55% of high performing enterprises are more likely to be extensively using mobile reporting tools to analyze data.  The following graphic compares mobile analytics adoption across high, medium and low performing enterprises.

top teams tap mobile analytics

  • Speed of deployment (68%), ease of use for business users (65%) and self-service and data discovery tools (61%) are the three top three priorities leaders place on selecting new analytics apps.  Mobile capabilities to explore and share data (56%) and cloud deployment (54%) are the fourth and fifth factors leaders mentioned.  The following graphic compares the decision factors that go into selecting an analytics app.

decision factor analytics app

  • Industries who have the greater analytics adoption today (over 50% of users active on apps and tools) include high tech (36%) and financial services (32%). Automotive (30%) and media & communications (30%) also have attained significant adoption.

adoption

  • High performing enterprises are 5.4x more likely than underperformers to primarily use analytics tools to gain strategic insights from Big Data. Leaders in high performance enterprises see the value of Big Data (76%) to a much greater extent than their lower performing counterparts (14%).   High performing enterprises are 3.1x more likely than underperformers to be confident in ability to manage data from internal systems, customers, and third parties.
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