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Opinions expressed by Entrepreneur contributors are their own.

You've probably heard this phrase ad nauseum: "No one ever got fired for buying from ." It speaks to one of the greatest challenges for most startups: Winning the trust that comes with having an established, recognized .

If this describes you, can help. In fact, businesses that prioritize it generate three times as many leads and see 30% higher growth than those that don't.

If you're not convinced content marketing is for you, here are four reasons it's important for businesses of all sizes  —  especially startups.

Related: Here's How to Strengthen Your Business's Content Marketing

B2B buying habits have changed

B2B buyers now demand a purchasing experience that minimizes their direct interaction with brands and maximizes their reliance on digital channels for information.

A recent study by Gartner found that B2B customers spend approximately 5% of their total purchasing time interacting with a supplier, with the majority devoted to independent research.

New buying behaviors favor established brands by virtue of their name-brand recognition and perceived authority. Yet startups can compete by producing high-quality, . Studies show that 47% of B2B buyers say thought leadership made them discover and purchase from a company not among the established leaders of a specific niche.

To ensure your content reflects the needs and journey of your buyers:

  • Survey existing customers. Try to understand their unique journey and the dynamics of their buying team.
  • Download sales team insights. Regularly gather and document sales-team insights from interactions with prospects.
  • Perform an audit. Audit your existing content, research, and knowledge bases.
  • Get third-party validation. Use credible third-party research specific to your niche.
  • Tailor content to audiences. Develop detailed buyer personas and map your content to their journey.

Content only works if it speaks to your customer. To help guide you, always start with voice-of-customer data to drive content strategy and messaging. Their feedback should drive everything, with industry research and empirical evidence providing support.

Related: Content Marketing Quick-Start Guide: 3 Things Your B2B Startup Should Publish First

Analytics make it possible to better understand your target customer

Today, analytics tools enable businesses to learn more about their target customer than ever before. Still, data analytics need content to drive value.

The more than 100 data points that Google Analytics tracks offer nothing if you can't attract audiences to your website. All those social media metrics? They're meaningless too without posts that drive impressions and engagement.

Content facilitates a learning process that enables your startup to survive and win. The more you produce, the more you find out about your target customer and what motivates them to take profitable action. This is important for any business, but especially startups.

To get the best insights from your content:

  • Set a regular publishing schedule. Establish a consistent cadence for publishing your various content offers (e.g. weekly blog posts on Tuesday and Thursday).
  • Make content cohesive. Cross-reference and cross-promote your content offers.
  • Learn and apply. Update your content strategy regularly with gained insights.

This last bullet matters most and surprisingly receives the least attention. If you capture analytics but never apply them, what's the point? So, set weekly team meetings that evaluate content performance and focus on improvement.

Related: Why Your Startup Content-Marketing Strategy Isn't Working

B2B buyers use large and diverse teams

As -based products and services become more common, B2B buyers are increasingly using large and diverse teams to make a decision.

Buying groups tend to:

While these attributes favor established brands, startups can get more consideration. How? By developing thought leadership that attracts attention, demonstrates authority, and makes buying teams smarter.

To Strengthen the chances your content resonates with diverse groups:

  • Develop different functional decision-makers. Develop content that targets the specific interests of different decision-makers, such as content focused on business value for executives and technical design for software engineers.
  • Develop full-funnel content. Produce a balanced mix of content that focuses on each stage of the buying journey (i.e. awareness, consideration, decision).
  • Target different learning styles. Diversify the format of your content offering to suit your buying team's learning styles and preferences (e.g. audio, video, graphic, written).
  • Enhance your visibility. Make your content available where your buying teams go for information.

The above activities depend on factors specific to your business and niche, including your buyer's product awareness and sophistication levels. Your buyer, and what drives them to convert, should drive everything you do.

Related: 5 Tips to Launch a Content Marketing Program Faster (and With Fewer Resources)

Startups are building recognized brands  —  fast

Brand recognition is an inherent weakness for most startups. Still, that doesn't mean they can't become a recognized name for their niche fast  —  with content marketing as their rocket fuel.

The fintech company Mint famously adopted a content marketing strategy that contributed to its rapid success. Before ever launching a product, it started a successful blog catering to its target customer and built an email list of 20,000 subscribers. It took them only three years to get acquired by for $170 million.

Building is most important in the startup phase, and content marketing is the most cost-effective tool to accelerate the process.

To accelerate your brand building, leverage content marketing that can scale:

  • Leverage third-party outlets. Tap into channels that maximize your reach and authority (e.g. byline articles in credible publications, speaking engagements, guest podcast appearances).
  • Engage influencers. Leverage influencers to help market your brand and content (e.g. guest blog post, guest podcast appearances).
  • Collaborate with partners. Partner with existing customers and/or partners to develop and cross-promote content (e.g. case studies, co-branded whitepapers).
  • Gate content intentionally. Balance ungated and gated content to drive brand awareness and leads.

The exact content strategy you pick depends (again) on your buyer. But you should also take into consideration your internal strengths. If you're a charismatic founder who naturally shines on stage, a keynote speech or video interview might offer the highest ROI.

Bottom line: Invest in a content marketing strategy

All signs point to one big takeaway.

Content marketing is a reliable (and much-needed) vehicle to convince customers to take a chance on you.

So take a chance on it. Show the world why you're better than all the job-saving IBMs out there.

Fri, 29 Jul 2022 04:00:00 -0500 Todd Stansfield en text/html https://www.entrepreneur.com/article/430822
Killexams : Why AI is critical to meet rising ESG demands

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Could artificial intelligence (AI) help companies meet growing expectations for environmental, social and governance (ESG) reporting? 

Certainly, over the past couple of years, ESG issues have soared in importance for corporate stakeholders, with increasing demands from investors, employees and customers. According to S&P Global, in 2022 corporate boards and government leaders “will face rising pressure to demonstrate that they are adequately equipped to understand and oversee ESG issues — from climate change to human rights to social unrest.”

ESG investing, in particular, has been a big part of this boom: Bloomberg Intelligence found that ESG assets are on track to exceed $50 trillion by 2025, representing more than a third of the projected $140.5 trillion in total global assets under management. Meanwhile, ESG reporting has become a top priority that goes beyond ticking off regulatory boxes. It’s used as a tool to attract investors and financing, as well as to meet expectations of today’s consumers and employees.  

But according to a recent Oracle ESG global study, 91% of business leaders are currently facing major challenges in making progress on sustainability and ESG initiatives. These include finding the right data to track progress, and time-consuming manual processes to report on ESG metrics.

“A lot of the data that needs to be collected either doesn’t exist yet or needs to come from many systems,” said Sem J. de Spa, senior manager of digital risk solutions at Deloitte. “It’s also way more complex than just your company, because it’s your suppliers, but also the suppliers of your suppliers.” 

ESG data challenges driving use of AI

That is where AI has increasingly become part of the ESG equation. AI can help manage data, glean data insights, operationalize data and report against it, said Christina Shim, VP of strategy and sustainability, AI applications software at IBM. 

“We need to make sure that we’re gathering the mass amounts of data when they’re in completely different silos, that we’re leveraging that data to Strengthen operations within the business, that we’re reporting that data to a variety of stakeholders and against a very confusing landscape of ESG frameworks,” she said. 

According to Deloitte, although a BlackRock survey found that 92% of S&P companies were reporting ESG metrics by the end of 2020, 53% of global respondents cited “poor quality or availability of ESG data and analytics” and another 33% cited “poor quality of sustainability investment reporting” as the two biggest barriers to adopting sustainable investing. 

Making progress is a must, experts say. Increasingly, these ESG and sustainability commitments are no longer simply nice to have,” said Shim. “It’s really becoming kind of like a basis of what organizations need to be focused on and there are increasingly higher standards that have to be integrated into the operations of all businesses,” she explained. 

“The challenge is huge, especially as new regulations and standards emerge and ESG requirements are under more scrutiny,” said De Spa. This has led to hundreds of technology vendors flooding the market that use AI to help tackle these issues. “We need all of them, at least a lot of them, to solve these challenges,” he said.

The human-AI ESG connection

On top of the operational challenges around ESG, the Oracle study found 96% of business leaders admit human bias and emotion often distract from the end ESG goals. In fact, 93% of business leaders say they would trust a bot over a human to make sustainability and social decisions. 

“We have people who are coming up now who are hardwired for ESG,” Pamela Rucker, CIO advisor, instructor for Harvard Professional Development, who helped put together the Oracle study. “The idea that they would trust a computer isn’t different for them. They already trust a computer to guide them to work, to deliver them directions, to tell them where the best prices are.” 

But, she added, humans can work with technology to create more meaningful change and the survey also found that business leaders believe there is still a place for humans in ESG efforts, including managing making changes (48%), educating others (46%), and making strategic decisions (42%). 

“Having a machine that might be able to sift through some of that data will allow the humans to come in and look at places where they can add some context around places where we might have some ambiguity, or we might have places where there’s an opportunity,” said Rucker. “AI gives you a chance to see more of that data, and you can spend more time trying to come up with the insights.” 

How companies can get started with AI and ESG

Seth Dobrin, chief AI officer at IBM, told VentureBeat that companies should get started now on using AI to harness ESG data. “Don’t wait for additional regulations to come,” he said. 

Getting a handle on data is essential as companies begin their journey towards bringing AI technologies into the mix. “You need a baseline to understand where you are, because you can make all the goals and imperatives, you can commit to whatever you want, but until you know where you are, you’re never gonna figure out how to get to where you need to get to,” he said. 

Dobrin said he also sees organizations moving from a defensive, risk management posture around ESG to a proactive approach that is open to AI and other technologies to help. 

“It’s still somewhat of a compliance exercise, but it’s shifting,” he said. “Companies know they need to get on board and think proactively so that they are considered a thought leader in the space and not just a laggard doing the bare minimum.” 

One of the key areas IBM is focusing on, he added, is helping clients connect their ESG data and the data monitoring with the genuine operations of the business. 

“If we’re thinking about business facilities and assets, infrastructure and supply chain as something that’s relevant across industries, all the data that’s being sourced needs to be rolled up and integrated with data and process flows within the ESG reporting and management piece,” he said. “You’re sourcing the data from the business.” 

Deloitte works with Signal AI on ESG efforts

Deloitte recently partnered with Signal AI, which offers AI-powered media intelligence, to help the consulting firm’s clients spot and address supplier risks related to ESG issues. 

“With the rise of ESG and as businesses are navigating a more complex environment than ever before, the world has become awash in unstructured data,” said David Benigson, CEO of Signal AI. “Businesses may find themselves constantly on the back foot, responding to these issues reactively rather than having the sort of data and insights at their fingertips to be at the forefront.” 

The emergence of machine learning and AI, he said, can fundamentally address those challenges. “We can transform data into structured insights that help business leaders and organizations better understand their environment and get ahead of those risks, those threats faster, but also spot those opportunities more efficiently too – providing more of an outside-in perspective on issues such as ESG.” 

He pointed to recent backlash around “greenwashing,” including by Elon Musk (who called ESG a “scam” because Tesla was removed from S&P 500’s ESG Index). “There are accusations that organizations are essentially marking their own homework when it comes to sorting their performance and alignment against these sorts of ESG commitments,” he said. “At Signal, we provide the counter to that – we don’t necessarily analyze what the company says they’re going to do, but what the world thinks about what that company is doing and what that company is actually doing in the wild.” 

Deloitte’s de Spa said the firm uses Signal AI for what it calls a “responsible value chain” – basically, supplier risk management. 

“For example, a sustainable organization that cleans oceans and rivers from all kinds of waste asked us to help them get more insight into their own value chain,” he said. “They have a small number of often small suppliers they are dependent on and you cannot easily keep track of what they’re doing.” With Signal AI, he explained, Deloitte can follow what is happening with those companies to identify if there are any risks – if they are no longer able to deliver, for example, if there is a scandal that puts them out of business, or if the company is causing issues related to sustainability.” 

In one case, Deloitte discovered a company that was not treating their workers fairly. “You can definitely fight greenwashing because you can see what is going on,” he said. “You can leverage millions of sources to identify what is really happening.” 

ESG will need AI and humans going forward

As sustainability and other ESG-related regulations begin to proliferate around the world, AI and smart technology will continue to play a crucial role, said Deloitte’s de Spa. “It’s not just about carbon, or even having a responsible value chain that has a net zero footprint,” he said. “But it’s also about modern slavery and farmers and other social types of things that companies will need to report on in the next few years.” 

Going forward, a key factor will be how to connect and integrate data together using AI, said IBM’s Dobrin. “Many offer a carbon piece or sell AI just for energy efficiency or supply chain transparency,” he said. “But you need to connect all of it together in a one-stop-shop, that will be a total game-changer in this space.” 

No matter what, said Rucker, there is certainly going to be more for AI-driven tools to measure when it comes to ESG. “One of the reasons I get excited about this is because it’s not just about a carbon footprint anymore, and those massive amounts of data mean you’re going to have to have heavy lifting done by a machine,” she said. “I see an ESG future where the human needs the machine and the machine needs the human. I don’t think that they can exist without each other.” 

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn more about membership.

Wed, 13 Jul 2022 08:00:00 -0500 Sharon Goldman en-US text/html https://venturebeat.com/applied-ai/why-ai-is-critical-to-meet-rising-esg-demands/
Killexams : Global Warehouse Management System Market (2022 to 2031) - Featuring Manhattan Associates, Oracle, Infor and PTC Among Others

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Global Warehouse Management System Market

Global Warehouse Management System Market

Dublin, July 28, 2022 (GLOBE NEWSWIRE) -- The "Warehouse Management System Global Market Report 2022" report has been added to ResearchAndMarkets.com's offering.

This report provides strategists, marketers and senior management with the critical information they need to assess the global warehouse management system market.

This report focuses on warehouse management system market which is experiencing strong growth. The report gives a guide to the warehouse management system market which will be shaping and changing our lives over the next ten years and beyond, including the markets response to the challenge of the global pandemic.

Reasons to Purchase

  • Gain a truly global perspective with the most comprehensive report available on this market covering 12+ geographies.

  • Understand how the market is being affected by the coronavirus and how it is likely to emerge and grow as the impact of the virus abates.

  • Create regional and country strategies on the basis of local data and analysis.

  • Identify growth segments for investment.

  • Outperform competitors using forecast data and the drivers and trends shaping the market.

  • Understand customers based on the latest market research findings.

  • Benchmark performance against key competitors.

  • Utilize the relationships between key data sets for superior strategizing.

  • Suitable for supporting your internal and external presentations with reliable high quality data and analysis

Major players in the warehouse management system market are Manhattan Associates, Oracle Corp., Infor, PTC, SAP SE, PSI Logistics GmbH, IBM Corp., Tecsys, Blue Yonder, Honeywell International Inc, Technology Solutions (UK) Ltd, HighJump Software, Synergy Ltd, Made4net and JDA Software Group Inc.

The global warehouse management system market is expected to grow from $2.39 billion in 2021 to $2.74 billion in 2022 at a compound annual growth rate (CAGR) of 14.77%. The growth is mainly due to the companies rearranging their operations and recovering from the COVID-19 impact, which had earlier led to restrictive containment measures involving social distancing, remote working, and the closure of commercial activities that resulted in operational challenges. The market is expected to reach $4.83 billion in 2026 at a CAGR of 15.15%.

The warehouse management system market consists of sales of warehouse management services by entities (organizations, sole traders and partnerships) which are used by companies to manage and control daily warehouse operations, from the moment goods and materials enter a distribution or fulfilment centre until the moment they leave. Warehouse management systems include inbound logistics and outbound logistics tools for picking and packing processes, resource utilization, analytics, and others.

The main warehouse management system offerings include software and services. Warehouse management system software are used to control and manage daily warehouse operations. The warehouse management system software helps in managing and controlling regular warehouse operations. It directs inventory in managing, picking, and shipping of orders, and guides the system automatically on picking and shipping items.

The different warehouse management system deployment modes include on premises and cloud. The warehouse management system functions include labor management system, analytics and optimization, billing and yard management and systems integration and maintenance, which are used for applications in transportation and logistics, healthcare, retail, manufacturing, food and beverage and other applications.

North America was the largest region in the warehouse management system market in 2021. Asia Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in this report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

Increasing demand from e-commerce companies for larger warehouses with better tracking and forecasting is expected to drive the warehouse management system market. The growing e-commerce industry requires continuous tracking of all the equipment and inventory forecasting to keep up the demand and maintain larger cargo movement.

For instance, a study from a research firm Knight Frank reported that the annual warehousing transactions in India are expected to increase from 31.7 million square feet in 2021 to 76.2 million square feet in 2026. Therefore, increasing demand from e-commerce companies is expected to boost the market during forecast period.

Technological advancement is a key trend gaining popularity in the warehouse management system market. Technological advancement is a discovery of knowledge that advances technology. For instance, in May 2020, a US-based provider of technology solutions for distribution centers launched the Manhattan Active Warehouse Management solution, which marks the world's first cloud-native enterprise-class warehouse management system (WMS). The new warehouse management system unifies every aspect of distribution and contains unified control, which allows management team members to quickly visualize, diagnose and take action anywhere in their supply chain.

The countries covered in the warehouse management system market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA.

Key subjects Covered:

1. Executive Summary

2. Warehouse Management System Market Characteristics

3. Warehouse Management System Market Trends And Strategies

4. Impact Of COVID-19 On Warehouse Management System

5. Warehouse Management System Market Size And Growth
5.1. Global Warehouse Management System Historic Market, 2016-2021, $ Billion
5.1.1. Drivers Of The Market
5.1.2. Restraints On The Market
5.2. Global Warehouse Management System Forecast Market, 2021-2026F, 2031F, $ Billion
5.2.1. Drivers Of The Market
5.2.2. Restraints On the Market

6. Warehouse Management System Market Segmentation
6.1. Global Warehouse Management System Market, Segmentation By Offering, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

6.2. Global Warehouse Management System Market, Segmentation By Deployment, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

6.3. Global Warehouse Management System Market, Segmentation By Function, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

  • Labor Management System

  • Analytics And Optimization

  • Billing And Yard Management

  • Systems Integration And Maintenance

6.4. Global Warehouse Management System Market, Segmentation By Application, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

7. Warehouse Management System Market Regional And Country Analysis
7.1. Global Warehouse Management System Market, Split By Region, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion
7.2. Global Warehouse Management System Market, Split By Country, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

For more information about this report visit https://www.researchandmarkets.com/r/zf30b

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Wed, 27 Jul 2022 15:58:00 -0500 en-GB text/html https://uk.finance.yahoo.com/news/global-warehouse-management-system-market-105800403.html
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