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  • admin 9:44 am on October 20, 2017 Permalink
    Tags: , Bringing, , , , , , ,   

    Bringing Artificial Intelligence to the Enterprise: Delivering Real Business Outcomes from Artificial Intelligence 

    After decades of promise and setbacks, Artificial Intelligence (AI) is experiencing a renaissance. AI is now solving problems in the enterprise with higher degrees of accuracy and in other cases, solving previously intractable problems.
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  • admin 9:51 am on June 14, 2017 Permalink
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    The Future of Marketing: Bringing Together Business and Education to Close the Skills Gap 

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  • admin 9:54 am on June 23, 2015 Permalink
    Tags: Bringing, InStore, , , PICKUP   

    Bringing Omni-Channel IN-STORE PICKUP To Life 

    Omni-Channel PrioritiesRetailers today are investing in new and different ways to deliver on the promise of right product, right time, right channel, for the right customer. Top retail delivery priorities include Ship-From-Store, In-Store Pickup, and In-Store Associate Ordering – and each is evolving at a different pace across the industry. Last month, I hosted the E-Tail East Summit in Atlanta and we explored these three topics.

    The next strategy for retailers to employ as part of their omni-channel consumer choice and convenience engagement model, is In-Store Pickup. With this fulfillment approach, the consumer gets the option of ordering online and picking up their products in-store for convenience, for immediate gratification, and to avoid shipping fees (although most retailers offer free shipping options).

    For the retailer, the consumer is in the store where they potentially purchase additional items. Also, the retailer is given the opportunity to engage the consumer in a positive, differentiated shopping environment and encourage return visits face-to-face (vs. email, etc).

    In a recent Forrester report, ISP was highlighted: “For some retailers, like Target, in-store pickup accounts for 10% of online sales. Store pickup is a key capability that retailers must embrace if they are to compete with online pure plays. 47% of consumers cited that they use store pickup to avoid online shipping costs, 25% use store pickup so they can collect their orders on the day they purchase them (thus avoiding the wait for shipping). From a retailer perspective, 52% of retailers cited inventory accuracy issues as a major barrier to the roll-out of these programs. With 25% of consumers using pickup as a means to obtain their purchase on the same day, it is perhaps no surprise that 41% of consumers expect to be notified that their order has been picked and is ready for collection in under an hour (18% expect their items to be ready in under 20 minutes).”

    Inventory accuracy is crucial to provide a good consumer experience.


    There are a number of key areas to consider when considering an in-store pickup strategy.

    Inventory Accuracy

    • Safety stock levels
    • Price discrepancies between online and in-store prices

    Customer Pick-up Location

    • Customer ease
    • 37% of shoppers purchase additional items when picking up in-store

    Store Ops / Training

    • Established protocols and training
    • Associate goals and metrics
    • Ensure pick and pickup process doesn’t interfere with in-store customers



    • Convenience of online shopping
    • Same day pickup
    • No shipping costs


    • 37% purchase additional products while picking up in-store
    • Leverage store assets
    • Increase foot traffic and upsell opportunity
    • Demonstrate unique and differentiated guest experience

    The post Bringing Omni-Channel IN-STORE PICKUP To Life appeared first on Industry Experts.

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  • admin 9:54 am on June 3, 2015 Permalink
    Tags: Bringing, , SHIPFROMSTORE   

    Bringing SHIP-FROM-STORE To Life 

    Omni-Channel PrioritiesRetailers today are investing in new and different ways to deliver on the promise of right product, right time, right channel, for the right customer. Top retail delivery priorities include Ship-From-Store, In-Store Pickup, and In-Store Associate Ordering – and each is evolving at a different pace within the retail industry. Last month, I hosted the E-Tail East Summit in Atlanta and we explored these three topics.


    Ship-from-Store (SFS) provides the most revenue impact to a retailer and is less visible from a fulfillment perspective to the customer. Ship-from-store should be priority #1 for every retailer for various reasons. First, ship-from store eliminates nearly all out-of-stock scenarios for the customer by providing access to chain-wide inventory online. This can lead to 20-40% incremental ecommerce revenue. SFS also facilitates faster delivery to customers. Typically when shipping from a DC, approximately 8% have a 1-day transit time; while SFS has 90% 1-day transit time (an 82% improvement).

    In a recent Forrester report, SFS was highlighted: “Out of retailers that support ship from store, 90% are expecting store-based fulfillment to account for up to 35% of their total online order volume. Eighty percent of these retailers also plan to enable up to 80% of their stores for store-based fulfillment. The business case for enabling store-based fulfillment spans revenue, operational, and customer satisfaction metrics. Ninety-three percent of retailers cited that enabling ship-from-store had resulted in a positive or significantly positive uplift in online revenue, 77% cited it had reduced or significantly reduced their fulfillment costs, and 88% cited it had improved or significantly improved their customer satisfaction metrics.” And SFS results in a 25-30% savings in shipping costs compared to shipping from a DC.

    There are a number of key areas to consider when considering a ship-from-store strategy.


    • Single view of inventory across the network
    • Accurate store level inventory
    • Safety stock levels
    • Automatic adjustments of “Available to Purchase” inventory levels

    Order Routing

    • Proximity to delivery address
    • Minimization of split orders
    • Inventory optimization / daily store limits

    Store Ops

    • Store set-up, protocols and procedures
    • Staffing strategies
    • Shipping SLAs and managing supplies
    • Managing pick up times / rules
    • KPIs and reporting


    • Intelligent order routing
    • Saleable Inventory: Item eligibility; Safety Stock Levels by order type; MIA – inventory discrepancies; In Flight Orders; Store Settings
    • Enabled fulfillment location settings
    • Weighted location preference sequencing
    • Max units/orders per day per location
    • Special orders (Gift Wrap, USPS, etc.)
    • Product sell-through/weeks of supply
    • Freight and labor expenses
    • Allocation rule variables
    • Split shipment rules
    • Expedite order rules
    • Max system allocation attempts
    • Inventory proximity to customers
    • Defining the store with “the most” inventory
    • PM and weekend allocations
    • Product/category sourcing priorities
    • Open-Close days/hours

    Benefits of Ship-From-Store


    • Expanded product assortment
    • Few “out of stock” / “back order” scenarios
    • Fast delivery (expectation of 80% within 1 day; 96% within 2 days)
    • Products “always available” when desired


    • 10-40% incremental ecommerce revenue (industry estimate)
    • Increase inventory sell through
    • Decrease markdowns
    • Optimize store assets and labor

    The post Bringing SHIP-FROM-STORE To Life appeared first on Industry Experts.

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  • admin 9:47 am on April 25, 2015 Permalink
    Tags: Bringing, , Groupon, Masses   

    Bringing Big Data To the Masses Groupon 

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  • admin 9:54 am on April 13, 2015 Permalink
    Tags: Bringing, , , ,   

    Bringing the DATA-DRIVEN BUSINESS To Life (Part 1) 

    CPGExploiting data for competitive advantage effectively is what differentiates leaders and followers in any industry. This is especially apparent in the world of Consumer Packaged Goods (CPG) and Retail. The leaders are going big – are investing in challenging their own internal business processes to find new ways of going to market across new channels, are investing in trial of new enabling technologies that enable business process change, and are investing in upping the skill sets of existing staff while infusing new ideas and concepts via a new echelon of talent in the analytics and data sciences space.

    Executives today have more data available from a variety of new channels and yet are challenged with transforming large volumes and varieties of data into actionable insights. In many cases across the industry “data rich,” “insights poor” prevails.

    While most executives acknowledge the value in looking to new and varied data sources for insight, most sense they have yet to extract value from data currently under their control. In some cases, the IT organization creates this perception by telling “the business” it has not clarified its requirements and therefore is “slow” in delivering reporting, analysis, and decision-support capabilities to the business in a timely manner. Business outcomes may only be achieved through business actions. Actions by the business require insights. Insights are derived from analytics. And analytics require the right data and tools.

    At the same time, all industries face immense challenges in the areas of growth and profitability. Globalization, consumer behavior, the “internet of things” and economic conditions conspire to place demands on organizations that existing data and analytic capabilities were never engineered to address. Many organizations are “stuck” with inflexible platforms that are expensive to maintain, even more expensive to upgrade or change, and difficult to sunset.

    Executives know better insight is possible and necessary to compete effectively, but are handcuffed by antiquated technology capabilities (e.g. Legacy hardware solutions).

    The result is dynamic tension between the business and IT and thus paralysis in many cases, leading business executives to pursue “shadow IT” projects reliant on 3rd parties (e.g. contractors, consultants, agencies) to solve specific business problems. This then results in siloed and disaggregated pockets of data yielding insights beyond the visibility (and governance) of other functional areas and the IT organization.

    Leading companies are finding ways to resolve this tension. Data-driven businesses are seizing the opportunity to make faster decisions using small subsets of relevant, timely, actionable data. They use cross-functional insights in ways never possible via traditional siloed business models. And it’s more than just enhancing productivity or reducing costs; becoming a data-driven business can help you identify insights that matter most to retailers, their shoppers and/or the end consumers, and use this knowledge to positively impact the relationship hand-offs.

    Becoming a data-driven business requires a shift in mindset and corporate culture first (aka. Leadership). Taking advantage of the data available within a business does not equate to arming your people with more metrics, reports and dashboards; it’s about delivering the most relevant and timely insights via the right analytics to make the best decision possible in a dynamic market where insights useful today may be useless tomorrow.

    Data-driven businesses are known for several key characteristics:

    • Executive Sponsorship: A business will only become a data-driven business if it is defined and communicated as a priority by the executive leadership team (not just the CIO). Note that as old-school, traditional backward-looking leaders move on and out of leadership roles, the data-driven business imperative will rapidly become a mainstay / baseline expectation as it has evolved with the eCommerce / Internet generation.
    • Integrated Data: Integrated data is typically the foundation for cross-functional business enablement; new sources of data are regularly and systematically evaluated for inclusion / exclusion in the integrated data environment.
    • Flexible Architecture: Data-driven businesses leverage integrated data and the key to effective use of this data is a data architecture that is flexible enough to allow for storage, harmonization, manipulation, summary, and more; and must enable everything from workflow tools to visualization tools and predictive modeling capabilities.
    • Test and Learn: Business teams have the right tools to access the data needed to drive decisions in their part of the business; this includes exploration, test, and trial/lab environment to explore new possibilities that may be found in the data.
    • Results Stewardship: Data-driven businesses find new ways to positively impact the business based and the results and best practices must be communicated to the larger organization so as to fuel continued evolution of the model.
    • IT-Biz Collaboration: Data-driven businesses are known for collaboration across the business / IT divide. This means IT supporting marketing and marketing leveraging IT for technology solutions. It means Supply Chain leans into IT to assist in getting new and different insights out of operational systems to enable change in route-to-market activities. IT must understand business priorities and the business must be willing and ready to lead change as it relates to new enabling technologies.

    The bottom line is that data-driven business leaders are able to make decisions their competitors cannot, driving increased revenue, improved profitability, and outperforming industry peers.

    The post Bringing the DATA-DRIVEN BUSINESS To Life (Part 1) appeared first on Industry Experts.

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  • admin 9:56 am on January 17, 2015 Permalink
    Tags: Bringing, , , , , , Valmet,   

    Valmet Corporation is Bringing More Value as a Data Driven Business 

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  • admin 9:54 am on January 15, 2015 Permalink
    Tags: Bringing, , , , Thunder   

    Mobile Marketing: Bringing Thunder to the Cloud 

    Verschlüsselung im E-Mail-MarketingOur mobile devices have become the most intimate electronic part of our lives, never leaving our sides. They’re connected to us, our needs and wants, our habits, our every need. Mobile is also the most critical tool for marketers to reach consumers on the go. Mobile platforms – smartphones and tablets combined – account for 60% of total time spent on digital media devices, up from 50% a year ago. Clearly, mobile is the way of the future, linking our lives to the rest of the connected world – our cars, our homes, and our health.

    That’s why Teradata’s acquisition of mobile software-as-a-service company Appoxee will do more than simply expand our portfolio or world class solutions – it will further our global vision of being the most customer-centric digital marketing company in the mix. While Teradata has offered mobile marketing capabilities in our solutions for some time, we’re adding exciting new technology and talent with the addition of Appoxee to Teradata Digital Marketing Center.

    Appoxee provides a powerful solution for mobile engagement – including push and in-app messaging, data collection, analytics and optimization with reach to millions of devices worldwide. Working with brands including Domino’s Pizza, Playtika (part of Caesars Entertainment), National Geographic, Fox, and Televisa, Appoxee has built reputation as a mobile innovator with market-leading features in areas such as message personalization and best time to send optimization.

    Marketing strategies centered on real-time, individualized, and contextual mobile communications will be the ones that break through the clutter. Recognizing that societal trends are shifting toward a mobile-centric marketing approach requires marketers to take a hard look at their campaigns and how they share information, especially with younger generations who are tomorrow’s most profitable customers.

    But, as with any communication platform, mobile cannot be viewed merely on its own. Managing and analyzing customer communications in real-time across email, landing pages, SMS, social media, and mobile push in concert with non-digital channels is crucial to a successful multi-channel approach.  Though it seems harped on much in the marketing tech space, it’s paramount for marketers in today’s data-driven age to be equipped with a powerful option for fully extending their customer engagement strategy to mobile platforms, tightly integrated with a digital marketing hub. Why? Quite simply, that’s where the customer is.

    We’re excited to welcome Appoxee to Teradata Marketing Applications. With better solutions for multi-channel mobile insights and communications, marketers will be able to orchestrate the experiences to customer growth and brand success.

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  • admin 9:51 am on December 2, 2014 Permalink
    Tags: Advice, , Bringing, , , ,   

    Advice for Bringing Hadoop Into the Enterprise Analytical Ecosystem 

    Where is the business world today in relation to the long-term effort to incorporate insights from big data? Winston Churchill put it best: “We are at the end of the beginning.”

    In the Silicon Valley ecosystem, Hadoop has been the rage for several years, but the larger business world is just starting to come to grips with how this technology will move from proof-of-concept into production. Some interesting points to note: Barclay’s just released a study (see “CIOs Uncertain About Hadoop’s Value: Barclays”) that indicates the adoption of Hadoop may happen gradually. CIOs are just not confident they can plug Hadoop into their data warehouse ecosystems and move ahead. Also, one of the findings from Gartner Analyst Merv Adrian’s research is that as tech executives gained more experience with Hadoop, they became less likely to think that it would eventually replace the data warehouse.

    dan woods blog image dec 1 sizedSuch a divergence between Silicon Valley and the rest of the business world, which will spend the big money on Hadoop, is perfectly normal. It is clear that big data has valuable insights and that Hadoop will be one of the most important technologies used to capture them. But it is also clear that the business world will come to use Hadoop in its own way for its own needs. The big data infrastructure at Facebook, Google, and Amazon is about as similar to what most businesses will use as a super computing grid is to a laptop.

    The challenge is to track innovation related to the use of big data in business both inside the Hadoop ecosystem and outside it. There are many projects that do very interesting things with big data. Consider Storm, a general purpose engine for processing real time streams of data that sits on top of Hadoop and Spark. There are many commercial extensions designed to make a Hadoop-based data lake work better and to bring Hadoop data directly to analysts.
    There are other technologies that can consume and process big data sets that haven’t stood still, such as parallel programming for scalable grids (Actian’s Data Flow), operational data capture and processing (Splunk), and of course the data warehouse (Teradata and others). All of these technologies can do much the same work as the MapReduce jobs that defined the first generation of Hadoop.

    Given the landscape, is it really credible to chart a future that is wall-to-wall Hadoop? No. I categorically reject the notion that Hadoop will solve all problems with big data so that you can just stop thinking, buy a cluster, and speed toward big data nirvana. I suspect that the CIOs in the Barclays study are equally skeptical and are wondering, “How will Hadoop and the data warehouse work together in an orderly fashion so that both discovery and production use of data can be supported?”

    The right answers for any particular company depends on the nature of your data, your workloads, your budget, the importance of innovation, and the available skills.

    For example, in retail stores if you use Splunk to harvest data from hundreds of in-store sensors into a sessionized form, a Teradata warehouse to add segmentation information, and then a graph analytics application in Aster to suggest ways of making personalized offers at signs inside the store, will the consumer reject those offers because they weren’t based on Hadoop?

    On the other hand, if you install a Hadoop cluster and can’t find anyone to make it work for you, you will never get any recommendations at all.

    The good news for CIOs and data analysts is that the integration of Hadoop into the data warehouse ecosystem is already being productized. The Hadoop vendors are announcing partnerships with data warehouse vendors at a breakneck pace. Why? Because customers want the vendors to take responsibility for the integration and deliver it as a feature. The data warehouse vendors are doing the same thing. Teradata, for example has partnerships with all three of the Hadoop distributions, Cloudera, Hortonworks and MapR, so that its customers can choose which they want to use. Teradata has also created technology like QueryGrid™ that allows one query to extract data from any number of sources, either in Hadoop clusters or in a data warehouse.

    All of this activity should give CIOs comfort. The first half of the problem of bringing Hadoop into a production data warehouse ecosystem is being solved. That’s the end of the beginning. The second half of the problem — the beginning of the end — is understanding how to craft all of this technology to solve the unique needs of your business. This is something that no vendor can do for you. In other words, the next stage of progress in implementing big data will not come from more intimate knowledge of technology, but from a detailed understanding of the data and how to make it useful for your business. My advice to for bringing Hadoop into the enterprise data warehouse ecosystem? Know thyself.

    Dan-Woods - blog sized for bio Headshot

    Dan Woods is CTO and founder of CITO Research. He has written more than 20 books about the strategic intersection of business and technology. Dan writes about data science, cloud computing, mobility, and IT management in articles, books, and blogs, as well as in his popular column on Forbes.com.

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