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  • admin 9:51 am on July 22, 2017 Permalink
    Tags: , , Curiosity, , , People, saves, ,   

    How Curiosity Saves Your Company … And Turns Your People Into Citizen Data Scientists 

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  • admin 9:51 am on June 13, 2017 Permalink
    Tags: Advances, , Breakthroughs, Forwarding, , , , People, Sanofi   

    Sanofi: Forwarding Medical Advances and Breakthroughs to Help People Have Better Health 

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  • admin 9:56 am on February 4, 2017 Permalink
    Tags: , People,   

    What People Really Do With IoT and Big Data 

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  • admin 9:46 am on February 19, 2016 Permalink
    Tags: , People, , ,   

    3 reasons why people, not robots, are key to data science 

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  • admin 9:51 am on February 2, 2016 Permalink
    Tags: , , , , , People, Valentine’s   

    5 Valentine’s Day Marketing Ideas : How to Make People Fall in Love With Your Brand 

    Ahh, it’s that time of year again: my Facebook feed is swamped with hearts and clichés.

    What is it about Valentine’s Day that makes us all so emotional? That makes us publicly announce our deepest and warmest feelings towards our loved ones?

    In some way or another we all want to love and feel loved. Not only on Valentine’s Day, but every day.

    Emotions help us connect. They help us inspire

    Do you want your brand to be able to connect and inspire with your customers? Here are 5 Valentine’s Day marketing ideas to help get you started.

    1. Make them feel special.

    When the sparks are flying in a relationship both sides feel the mushy side of love. Making your partner feel special and loved is what puts a fire in your relationship. As a brand you can show your love in a few different ways:

    1. Send out individualized messages.

    As a relationship grows, so does ones knowledge of their partners likes and dislikes. Just like you would not treat your current relationship like previous ones, this applies with customers too. Send email campaigns and push notifications that are personalized and make the customer feel important and valued.

    2. Make them laugh

    Why did the marketing couple decide not to get married?

    This was because they weren’t on the same landing page.

    Humor is always a wonderful way to connect with people. Make them laugh or smile and they will come back for more. As it’s said, “laughter is the best way to make somebody’s heart beat”.

    3. Send them love notes and poetry.

    That’s right you heard me. Brands can also send their customer poetry and show them how much they care on Valentine’s Day. In fact, last year Starbucks did that just.

    Strabucks cofee

    Source: SocialBro

    2. Surprise them

    We all love gifts and gestures, especially when we don’t expect them. The bigger the gesture is, the better we feel!

    A few ideas for surprises and gifts that will make your readers happy:

    1.Special limited time offers.

    2.Offer a free gift.

    Offer a gift

    Source: Windsor Circle

    3. Discounts online or in-store.

    4. Run a Valentine’s Day contest resulting in the winner getting a wonderful prize.

    5. Offer free shipping.

    Offer free shipping

    Source: Windsor Circle

    3. Take an active role in the relationship

    Just like a partner expects you be an active, your customers expect it too. Give them feedback and guide them through the buyer journey. If they forget an item in their cart send them a loving reminder. If they bought an item and you know that another item would be a perfect match to complete the purchase, let them know and they will appreciate it.

    4. Innovate

    Like in any relationship, don’t expect your customers to stick around if you keep doing the same things. Be creative, excite them and stand out from your competitors in order to keep your audience entertained and intrigued. Keep them on their toes and excited to see what your brand is up to this time. Take Scribbler for instance. They used their blog to have customers share their definition of love. Via your Scribbler account you were able to tweet your answer. This simple act was a great way to generate leads and engage their customers in a fun and interactive way.

    Marketing iteractive

    Source: HubSpot

    5. Know Your Partner

    Just like in dating, the more you know about someone, the better you will be at pleasing them. Take into account past behavior and make your marketing campaigns tailored to the users’ preferences. Take a look at last year and see what customers have purchased in the past and use this data to target those customers correctly.

    Did you love this post? Then share it to make me feel the love. Who knows – you might end up getting a surprise from us like a free trial offer of our services.


    The post 5 Valentine’s Day Marketing Ideas : How to Make People Fall in Love With Your Brand appeared first on Teradata Applications.

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  • admin 9:55 am on December 1, 2015 Permalink
    Tags: Accounting, , People, Process, , Utopia   

    A One Day Accounting Close? Utopia via People, Process, & Technology 

    The pressure for an accelerated accounting close can be relentless, as evidenced by the $ 1.3 billion Toshiba accounting scandal this spring. The electronic manufacturing giant admitted it had overstated profits by $ 1.3 billion going back to fiscal 2008/2009. An accounting probe in July led to the CEO and several board members resigning and a 30 percent slide in shares of Toshiba stock, and found that the company suffered from dysfunctions in governance.

    As senior financial leader Doug Ryan has said, the theoretical, achievable limit for the monthly accounting close is one day. That might be achievable for every business regardless of size, industry, or consolidation complexity in a near-perfect world with unlimited resources, but as we know, that utopian world doesn’t exist.

    Conventional wisdom generally pegs an optimal accounting close period at five business days. For companies who have overcome some of the more common hurdles to meeting that goal—such as cluttered or poorly defined accrual processes or an inability to track results on at least a near real-time basis—most find that each close process reduction is never enough. Both public and private companies must fulfill multiple, complicated financial reporting packages quickly and efficiently, while balancing competing internal and external reporting requirements and deadlines. Simultaneously, senior management needs fast, transparent close results that deliver meaningful insight that can guide their decisions.

    No Single Technology Is a Silver Bullet
    Technology can certainly help overcome some of these challenges, but it’s no panacea. There are many companies who install a helpful point solution or even an analytic database, score a quick win, and then find themselves facing new calls for close-process transformation within less than a year because they only accounted for technology and not people and processes. In my experience helping major enterprises optimize their close processes, a sustainably successful approach starts with recognizing the limits of technology.

    I see many data-driven finance departments using a single data repository to accelerate and lower the cost of monthly close processes. A single repository provides business units with faster access to local results, which simplifies local reporting requirements and prompts early error identification and correction. Business units spend less time reviewing because they have earlier visibility throughout the month. The corporate consolidations process is simplified through accessible transactional and sub-ledger details, which reduces the need to ask the field to clarify results.

    As important as these technical enablers are, technology is ultimately only one-third of the close-to-report cycle equation. A successful, holistic approach must account for people, process, and technology. How does your company rate on these close-to-report cycle dimensions?
    • Are roles and responsibilities in the accounting organization clearly aligned to every stage of the close process?
    • Are the events in the close calendar defined in a way that clearly assigns accountability back to specific individuals/roles?
    • How clearly is communication coordinated across all those involved in each stage of the process?
    • Are the activities throughout the close properly sequenced?
    • Is the process obstructed by manual steps occurring outside of the transactional-processing and reporting systems?
    • Are issues identified and analyzed in a way that resolves root causes?
    • Are the same processes/steps performed “because we’ve always done it that way” without questioning why?
    • Are current technologies fully utilized?
    • Are employees sufficiently trained and knowledgeable in the technologies that enable their part of the close process?
    • Can current technologies enable reduced “time to insight” through real-time or near real-time views of actual results?

    Technology will always matter, but it is most “sticky” when applied as part of a holistic approach. Companies like Toshiba looking to rectify breakdowns in their close processes and related governance mechanisms need to address the people, process, and technology factors that enabled such materially inaccurate reporting in the first place. In every company’s drive to accelerate the close process and head off a similar crisis, finance departments must think comprehensively if they hope to shorten the distance between reality and utopia.

    jay humphries bloggerJay Humphries is a Senior Pre-Sales Practice Manager within Teradata’s Data Driven Finance Center of Expertise. In his current role, Jay is focused on the intersection of finance, accounting and analytics in the Manufacturing and Oil & Gas industries. Prior to Teradata, Jay served in many roles to help organizations become more technology and data-driven, in areas such as management consulting, strategy, process improvement and ERP implementations.

    The post A One Day Accounting Close? Utopia via People, Process, & Technology appeared first on Data Points.

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  • admin 9:52 am on May 8, 2015 Permalink
    Tags: , Considered, Greatest, People,   

    One Day People Really Will Be Considered Our Greatest Asset 

    Throughout or working lives, we’ve heard the cliché from every Board member at some point or another: “people are our greatest asset”. But too many times it’s come before a round of redundancies or during a time of financial turbulence or just as something to say when a new CxO is in front of shareholders. Mostly, we have the feeling that it doesn’t actually mean anything.


    In utilities, we all understand that there is a skills gap. Globally. Engineers and experienced technical staff are retiring faster than we can attract new ones. Sure, people are working on the problem. There’s a real focus on increasing Science, Technology, Engineering & Mathematics (STEM) capabilities from organisations such as the STEM Education Coalition in the US. Last year, UNESCO launched the Global STEM Alliance.

    That’s all good news. But what I find even more heartening is that in recent times, I see evidence of utilities businesses not only supporting this sort of 3rd party initiative, but actually doing something internally in their organisations to value their people more, manage them better and actually treat them as that asset they’ve always told us about.

    UK Utility Scottish & Southern Energy is a great example. In April this year, they published a report that values their people at £3.4BN. They say it’s a first for a UK company. I can believe it. And it’s not just a PR exercise. Yes, they’re becoming a more media-savvy business (quite a step for a utility, remember…) and their HR Director blogs relatively frequently. But that is kind of the point: he’s not blogging about energy bills or keeping the lights on. He’s blogging about people. Their people.  I like that.

    Here’s a different example.   In the US, a long-term Teradata customer is taking another approach to more actively understanding and valuing their people. Xcel Energy began their journey with Teradata looking at meter-to-cash analytics. Since then, they’ve expanded their data & analytics capabilities into many parts of the business – most recently into HR. They’re now actively using the data available to them to create and deliver strategic workforce planning.

    And not before time: their analysis showed 44% of Xcel Energy’s workforce was already within 10 years of retirement. Clearly, time to act! Now, Xcel has the ability to more accurately predict employee churn, address talent gaps before they become a greater issue, and better inform leadership of workforce trends. Good news.

    Of course, these are only two examples in a huge, worldwide industry. But I believe they’re indicative of a growing trend. In utilities, as well as in other STEM industries, I think we are seeing the beginnings of recognition that people really, really might actually be our greatest asset. Just like we always said they were.

    If you’d like to hear more about what Xcel are doing on data-driven HR and people management, I can recommend the webinar they recorded earlier this year. Or, if you’d like to learn more about how Teradata can help you turn those tired old “people…” clichés into something real and valuable, we’d love to hear from you!

    David Socha is Utilities Practice Manager at Teradata International. He works with local and account-focused teams to bring Teradata’s unrivalled data and analytics capabilities and knowledge to the International Utilities sector. Connect with David Socha on Linkedin.

    The post One Day People Really Will Be Considered Our Greatest Asset appeared first on International Blog.

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  • admin 9:46 am on February 20, 2015 Permalink
    Tags: , , , Energys, , , People, , , ,   

    Using Analytics to Power Your People How Data Drives Xcel Energys Insights for HR and Workforce Management 

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  • admin 9:53 am on February 8, 2015 Permalink
    Tags: , , Normal, Normalization, Organizing, People,   

    Normalization for Normal People … Organizing Data for Business Value 

    Are you a business person or executive involved in a data warehouse project where the term “normalization” keeps coming up but you have no idea what they (the technical IT folks) mean? You have heard them talk about “third” normal form and wonder if it is some new health fad or yoga position.

    In my prior blog “Modeling the Data” I talked about how data integration is necessary to address many of your business priorities and that one of the first steps in data integration is to organize your data into tables. A “data model” is a graphical representation of that organization which serves as a communication tool between and within the business and IT as shown below.

    Data Model Example – Accounts and Individuals Reflect Business Rules

    Data Model Example – Accounts and Individuals Reflect Business Rules


    So now we get to normalization. Normalization is the process that one goes through to decide in which table a type of data belongs. Let’s take a simple example. I have two tables – one contains loan account information and another contains information about individuals who may be customers (see above Figure). I have a data type called “birth date.” During the normalization process I will ask “What does this data type describe?” Does it describe the account or does it describe an individual? This answer is simple – it describes individuals. You may think that this is a piece of cake. Well, not so fast. Which table is the best fit for the data type “birth date” may be obvious to us, but many times the “best table fit” for a type of data may not be so obvious and hence you need definitions for those data types.

    One example of an ambiguous data type is “balance.” Does this “balance” describe a point in time for an account? Or does it describe the sum of the balances for a group of accounts at a point in time? Maybe it should be “average balance over a time period.” Maybe it is high balance or low balance or a limit at a point in time. Maybe it is the cleared balance or a ledger balance. Maybe it is a summation of all the deposit balances held by one person at a point in time. A data model is not complete unless all its components (tables and columns) have definitions.

    The normalization process can get more involved when we talk about first, second and third normal forms (and sometimes fourth and fifth). Using the birth date example, if the type of data (e.g. birth date) describes the complete meaning of the table then it is third normal form. In the above data model example, if I put birth date into the INDIVIDUAL ACCOUNT table then that would not be in third normal form because the birth date describes only part of the meaning of that table – the individual part. In this case it would be in only second normal form. By putting birth date into the INDIVIDUAL table it is in third normal form because it describes the complete meaning of the table. In most cases we take a model to third normal form but not fourth or fifth.

    Why Normalize Your Data?

    Why is it important to normalize your data? There are two basic reasons. (1) The first is to eliminate redundancy. When you bring your data together from different sources you will inevitably have duplications in data values for the same data type across the source systems. One example is the same person may have their name spelled differently on a loan account versus a deposit account. That person does not have two names, the name just needs to be represented in one place with one value in the right place in the integrated database. (2) The second reason is to make sure that the data is organized into tables in a way that reflects the business rule – our example of birth date describing the individual and not the account. Putting data where they logically belong will make it easier and more cost effective to maintain over the long term.

    In Summary

    So the next time someone brings up the concept of normalization think about the buckets of data you have in the enterprise, how you need to bring it all together so you can answer those tough business questions. Finally, when you bring it together, you need to eliminate redundancy and organize data in a logical way that makes sense to the business so that your efforts and design will last over the long term. Normalization is one of the processes to get you there.

    Kalthoff Work resized Photo (2)

    Nancy Kalthoff is the product manager and original data architect for the Teradata financial services data model (FSDM) for which she received a patent. She has been in IT over 30 years and with Teradata over 20 years concentrating on data architecture, business analysis, and data modeling.

    The post Normalization for Normal People … Organizing Data for Business Value appeared first on Data Points.

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  • admin 9:55 am on November 22, 2014 Permalink
    Tags: , integrate, Ownership, People, , Turf,   

    Integrate Data, Processes & People: End Data Ownership Turf Wars 

    The biggest thing I’ve realized over the past couple of months, other than Tony Romo is one of the best NFL players I’ve ever seen — is the fact that data ownership is still a huge problem for companies of all types. Tony’s numbers keep getting more impressive game by game – and likewise the pace of data streaming into organizational information channels rises by the hour.

    Romo aside, the dramatic growth of data volume only seems to rekindle data ownership issues among so many internal departments, who don’t or won’t see the advantages of sharing information. Maybe call it data ‘possessiveness.’ I really thought, and I have said in numerous presentations over the summer, that we’d solved the data ownership problem. To begin with, the industry seems to have understood the value of data integration and optimization, and a ‘single view of the customer,’ once just a hazy vision in the distance, was now becoming a technological reality, so isn’t ‘data sharing’ a no-brainer?

    But after presentations at a few conferences this fall, including Teradata Partners, folks have come to say things like, “Everyone in all of our marketing areas wants data from the Customer Insights group — but they won’t play nice and share it.” Others have made similar complaints at reception chats or over lunch. These little ‘data dramas’ and ‘turf tussles’ surprise me.

    What also continues to surprise me is the lack of marketing participation at many IT gatherings. When I lead a session on how to use big data in marketing, the audience is usually 90% data scientists or IT specialists and 10% marketing. Sunday, in my well-attended session at the Partners event, it was zero marketers. What’s up with that? Where are those savvy ‘data-driven’ marketers?

    On to Monday, where we held a lunch for 30 retailers and CPG firms. Other than the one analyst from IDC, the rest were from companies like Safeway, Target, HEB, Williams & Sonoma, Hallmark, etc. While some work in marketing, none viewed themselves as ‘marketers’ – they were data scientists or IT specialists. Great people, truly interested in Dynamic Customer Strategy, and like Sunday’s session, it went very well. But again, no CMOs, no marketing directors, no merchandisers. Baffling!

    Trend-watchers report that marketing is supposed to be the biggest spender on IT by 2017, outpacing the IT department. Somehow, the CMO is supposed to become the most proficient IT buyer on the planet. So when does the foundational due diligence take place?

    Reading a few white papers or looking at where a particular solution is — in some magic matrix — is not sufficient. Someone thinks, “Oh, we can make money with marketing automation tools here. Let’s get one and get some data and go to work.” And then they demand the data from the data group, or from some other group so they can get their work done without thinking about the greater good. Sharing data always results in the greater good, right?

    Data possessiveness has become the modern tragedy of the commons, a phrase coined to describe the overgrazing that would occur when everyone shared a common pasture (like the Boston commons).

    In this modern-day tragedy, there are two outcomes. First comes technology bloat, and with technology bloat comes lots of little not-playing-well-with-others data sets and an insufficient data strategy. Maybe they can import the data in — but not out.

    In case you are unfamiliar with the term, technology bloat was coined by my former student and now consultant Ben Becker (beckerstrategies.com) to describe the common situation of multiple overlapping software solutions. In environments where data silos and turf battles over applications exist, technology bloat is a huge challenge for IT: Multiple systems to support when one would do, budget-crushing agreements when rationalization would be less expensive, and so on and so on.

    That’s why I found it interesting that Michael Koehler, Teradata’s CEO, emphasized integration as the key watchword for 2015. Integration clearly is a play that works well for Teradata, especially with its full suite of solutions. But when marketing is spending more than IT on IT and doesn’t know how, there’s a tall challenge.

    Another causal factor of technology bloat is ‘how’ marketing budgets and spends funds for IT. The budget to acquire may not even be an IT budget but come out of monies allocated to a particular program or profit center. The campaigns budget, for example, might be used to buy a campaign management tool. As long as revenue targets are hit, all is well from a budgetary perspective, at least as far as marketing management is concerned. Of course, no matter that it’s the third campaign management tool that the organization purchased.

    Similarly, there’s the revenue ownership problem. In spite of attribution modeling that can weight the effectiveness of each element in the marketing mix and apportion revenue accordingly, each profit center is unwilling to share revenue or customers. The result is customers who delete and ignore every marketing message from their former partners who now over-market because they won’t/can’t share data. In my department alone, I know of at least three different CRM systems.

    Moreover, marketers just want to do marketing, and especially the cool marketing. I get that. It’s fun to see marketing strategy actually lead to revenue, whether you’re in B2C and actual sales are immediately triggered or B2B and the work is mostly above the funnel.

    I suspect, though, that the problem is greater in B2B. When we did the study in retailing earlier this year, we were far less likely to identify data ownership as a bottleneck. Retailers are more mature than B2B in the whole data thing anyway, but there are also fewer marketing areas. B2B companies tend to be organized by product or vertical market and each operates as a separate business unit. Marketing departments or teams proliferate, and that leads to technology bloat etc.

    While the simple answer might be that IT should be making more decisions, I don’t see that as realistic. And if Koehler is correct that we’re in for a period of integration, then I suspect that will mean consolidation of tools and applications into suites. What’s interesting to me is that Teradata seems to be the lone voice, even among full-suite providers, crying out to end technology bloat.

    However, I agree that a period of integration is coming. When the CIO can demonstrate to the CMO how integration can improve revenue through better data and marketing strategies while reducing costs (and in that order), most CMOs will make that move.

    Data possessiveness will fade as the benefits of sharing integrated data become ubiquitous and irresistible. Data dramas will cease, and marketers will more enthusiastically participate in IT conferences.

    It’s called teamwork – something Tony Romo totally understands.

    best tanner blog bio 1-1




    Dr. Jeff R. Tanner is Professor of Marketing and the Executive Director of Baylor University’s Innovative Business Collaboratory. He regularly speaks at conferences such as CRM Evolution, Teradata Partners, Retail Technology, INFORMS, and others. Author or co-author of 15 books, including his newest, Analytics and Dynamic Customer Strategy, he is an active consultant to organizations such as Lawrence Livermore National Laboratory, Pearson-Prentice Hall, and Cabela’s.

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