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4 things executives should know about AI and data science

 4 things executives should know about AI and data science

Artificial intelligence, machine learning, and deep learning are buzzworthy terms in the world of business, ranging across channels from customer service to finance and beyond. Because big data is big news, companies want to implement AI to improve their businesses — but some are making the mistake of trying to layer in artificial intelligence without the basis in analytics and data that allows AI to make a true impact.

Other companies — those with a strong foundation in analytics, possessing a store of data to work from — can utilize AI with great success. According to the Harvard Business Review, “companies with strong basic analytics — such as sales data and market trends — make breakthroughs in complex and critical areas after layering in artificial intelligence.”

AI innovations like those aren’t possible without the right data and specialized data science staff who know how to use it. The following are four lessons that vanguard businesses have learned about the intersection between data and deep learning — lessons you can apply to your organization as you layer in your own artificial intelligence algorithms.

1. You have the data you need, but aren’t using it yet

If you have a successful business model making significant revenue, chances are you already have a ton of data available to you about your customers — what they’ve purchased, when they purchased it, how they prefer to be contacted — collected from common customer interactions. If you aren’t using this data or centrally collecting it for easy access, you’re wasting a resource that can add efficiency to your organization by providing a better, more personalized experience for your customers.

2. Creating new data is as important as using existing data

Too often, the traditional approach to analytics or data science is beholden to data you already have. As data science evolves, the creation of new, more applicable data and the capture of previously underutilized data are becoming more important. Business processes helped by artificial intelligence are only as good as the data you feed into that AI, which means locating and creating the right data is essential.

3. Data and information availability empowers autonomy

Historically, a business’ success has largely depended on in-company experts who knew the business model very well — high-level employees who have been with the company a long time, who understand the business and can act as resources, and who generate intuition from experience. This “executive intuition” is an incredibly valuable resource, but many employees in larger organizations do not have the experience necessary to garner this intuition, and not every employee has access to those veteran experts who do have the intuition.

Though teamwork is essential to good business, you also want everyone in your organization to be as autonomous as possible. When you use data correctly, you take the information that comes in over time, capture it, and make it available to whoever might need it. Data science can elevate executive intuition, empowering more decision makers. Then, moving forward, your organization can grow from a small group of experts making decisions based on experience and intuition to a larger group of employees making decisions based on quantitative measures.

4. Successful data science requires specialization

To properly make use of your data, you should build a functional team of specialists focusing on different aspects of data science and its applications. One data scientist with a basic understanding of different aspects of the discipline can put you in a situation where you have a jack-of-all-trades and a master of none. Recommended areas of specialization include data visualization, data cleansing, and artificial intelligence algorithm creation.

Artificial intelligence can help you be much more precise in the business decisions you make on the macro and micro levels, no matter how your business interacts with customers. To achieve that precision, though, you need to collect, create, and organize your data so that it becomes one of your organization’s greatest assets. The other greatest asset? The data science experts who make sure that your data and artificial intelligence are doing the most they can for you.

Landon Starr leads the data science organization at Clearlink, which includes the information management, advanced analytics, reporting, and conversion rate optimization teams.

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Big Data – VentureBeat

Don’t Forget to Do These Four Things at Summit EMEA 2018

Blog Images 1 300x225 Don’t Forget to Do These Four Things at Summit EMEA 2018

Summit EMEA is almost here, and we’re eager to join everyone at the expo. As a returning Gold Sponsor, we’re excited to share our expertise with the Dynamics 365 community. We love being around other Dynamics 365 enthusiasts, and that’s why today’s blog is all about helping you make the most of this experience. Here are four things you need to see and do while at Summit EMEA 2018:

4. Check out the PowerObjects Booth

PowerObjects is known for having fun at conferences, and as part of that fun, we’ll be showcasing how the Internet of Things connects to Dynamics 365 to create positive customer experiences. Just how will we be doing this? You’ll have to stop by the booth to find out!

*Pro Tip: Follow us on Facebook to see updates and booth sneak previews!

3. Learn About Dynamics 365 from Worldwide Experts During Sessions

PowerObjects is recognized as Microsoft’s 2017 Worldwide Partner of the Year for Dynamics 365 Consulting and Systems Integration. Our team is leading 8 separate breakaway sessions to showcase our expertise. Visit the link to learn more about each session including times and locations.

  • Designing Dynamics 365/CRM 101
  • Let’s Get Started with IOT and Dynamics 365
  • A Server-less Configuration-first Integration Platform for Dynamics 365
  • Office 365 Integrations: OneNote, SharePoint, OneDrive and More
  • Business Activity Monitoring: How to Build Simple BAM for Dynamics 365/CRM Using Microsoft Cloud Technologies
  • Cafe X and USD: An Explosive Mix
  • End to End Customer Service in Dynamics 365
  • DAX 101 for D365/CRM and Power BI
  • Building Asynchronous Integrations with MS Portals

2. Win Giveaway Items at Booth H3

We’re giving away plenty of exciting things from gift cards to jackets. Be sure to stop by booth H3 early to claim your giveaway and learn how you can be entered for a chance to win a Microsoft Surface!*

*While supplies last.

032818 1619 DontForgett1 Don’t Forget to Do These Four Things at Summit EMEA 2018

1. Join Our Partner Showcase Focused on Road Mapping Your Implementation

Check our page to learn more about this session. Our Dynamics 365 experts will be guiding you through your end-to-end journey with Dynamics 365. Come learn and get your questions answered around best practices, common pitfalls to avoid, and learn what it’s like to partner with PowerObjects – Microsoft’s 2017 Worldwide Partner of the Year for Consulting and Systems Integration.

We can’t wait to join everyone at Summit EMEA for three days packed with sharing knowledge and love for Dynamics 365. To learn more about PowerObjects’ sessions or to register for Summit EMEA and save 10%, check out our official Summit EMEA 2018 page.

Happy D365’ing!

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PowerObjects- Bringing Focus to Dynamics CRM

5 Things You Might Have Missed from the Mercedes-AMG Petronas Motorsport Preseason

M147573 5 Things You Might Have Missed from the Mercedes AMG Petronas Motorsport Preseason

With everything happening with the Mercedes-AMG Petronas Formula One team, you’d think the season has started already.

In the last few weeks, there’s been a lot of exciting preseason events for the Team. From the launch and testing of the new W09 to a new partnership to the team receiving an award at the “Team of the Year”, to the unveiling of the Petronas R&T Centre, Mercedes-AMG Petronas Motorsport has been quite busy getting ready for the upcoming F1 season.

The launch of the W09 EQ Power+

Mercedes-AMG Petronas Motorsport launched their new car for the 2018 F1 season, the W09 EQ Power+. Over 1,000 people were involved with the redesign of the car,improving the car, finding more speed, and tackling the regulation changes. A few of the notable changes are regulatory for 2018, including the halo (a device aimed at protecting the driver’s head from incidents), the removal of the shark fin engine cover, and T-wing aero devices.

As a result, there is a much-reduced fin on the back of the engine cover and no big T-wing. The new car is also a lot more slender than the W08 in order to improve the airflow around the car to generate more downforce. While the vast majority of the W09’s changes are not clearly obvious and are small in isolation, they add up to make a huge difference in the performance of the car.

Preseason Testing

All teams registered for the season travel to a designated circuit (in this case, it was Circuit de Barcelona-Catalunya in Spain) a few weeks before the first race to test out their newly-designed cars through their paces over two intense four-day periods. This specific track has been the home to preseason testing for many years due to its challenging nature, a wide range of characteristics, and clement weather.

Over the eight days of testing, the W09 completed 1,040 laps for 4,841 kilometers. The car took 16,640 corners, had 46,800 gear changes, and 41,600,000 fuel injections. Testing has given the Team plenty of data and information to study and dissect before the season begins to make any necessary adjustments to the car’s performance. With TIBCO’s technology, Mercedes-AMG Petronas will be able to use analytics to ensure that the car’s design and testing infrastructure delivers the best outcome.

“Team of the Year” award at the Laureus World Sports Awards

Mercedes-AMG Petronas Motorsport received the “Team of the Year” award at the Laureus World Sports Awards. The Team was up against numerous other nominees, including French Davis Cup Tennis squad, Champions League winners Real Madrid, NBA Champions Golden State Warriors, Super Bowl victors New England Patriots and the New Zealand America’s Cup team.

The Team was nominated for the fourth consecutive time, but this was their first time winning it, extending their 2017 championship success. Mercedes-AMG Petronas Motorsport’s win was also the third time a Formula One team has won an award in its 19-year history.

Partnership with Tommy Hilfiger

Mercedes-AMG Petronas Motorsport announced a new partnership with apparel company Tommy Hilfiger. As Official Apparel Partner of the team, Tommy Hilfiger is supplying the Team with brand-new race, travel, factory, office, and hospitality clothing. In light of the partnership, Tommy Hilfiger’s Spring 2018 collection and campaign nods to the fusion of fashion and F1. Lewis Hamilton was also named one of Tommy Hilfiger’s Global Brand Ambassadors for men’s, including Hilfiger Collection, Tommy Hilfiger Tailored and Tommy Hilfiger Menswear, Underwear and Swimwear.

The unveiling of the R&T Centre

Mercedes joined Petronas in Turin, Italy, for the opening of their brand-new $ 60 million Global Research & Technology (R&T) centre. This centre will be its global R&T hub and latest centre for of excellence — home to automotive and technology testing capabilities and expertise. The facility will play a significant part in the development of fuels for the next generation of road car engines, using technology tested and proven on the race track through its partnership with the team.

Petronas is responsible for the design, development, and delivery of the Fluid Technology Solutions (FTS) that have helped power the team to four consecutive Drivers’ and Constructors’ titles.

Watch as Mercedes-AMG Petronas Motorsport kicks off the 2018 F1 season in Melbourne this weekend at the Australian Grand Prix.

See how TIBCO’s partnership with Mercedes-AMG Petronas given them a competitive advantage with the TIBCO Connected Intelligence platform and System of Insight.

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The TIBCO Blog

10 Things about LinkedIn Sales Navigator a CRM Admin Needs to Know

LinkedIn Sales Navigator 300x225 10 Things about LinkedIn Sales Navigator a CRM Admin Needs to Know

In this blog, we will review the 10 things a CRM Admin needs to know about LinkedIn Sales Navigator and walk through some settings.

If you would like to learn more about the LinkedIn Sales widget, please check out this link: LinkedIn for Microsoft Dynamics CRM Widget – Overview. We recommend that you review the Microsoft Dynamics 2016 and Office 365 Installation Guide as well. If you are unfamiliar with the LinkedIn CRM Sales Widget, below is a very brief illustration because we are going to talk about Sales Navigator today!

The LinkedIn for Microsoft Dynamics 365 Widget works with the Accounts, Leads, Contacts and Opportunity entities. The widget allows a user to see a LinkedIn Member Profile and Company Profile as sections on the entity form. How does it work? Well, while creating a Lead, the widget lets the user search LinkedIn.com directly from the Entity form and users can view information from LinkedIn.com about the Lead’s LinkedIn Member Profile. Below are a couple of screen shots.

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If you want to know more about the LinkedIn Sales Widget, please see our video Dynamics 365 In Focus: LinkedIn Sales Navigator and read our blog How Microsoft’s Acquisition of LinkedIn is Revolutionizing the Sales Game for Dynamics 365 Users.

So, what is the Sales Navigator CRM sync about for a CRM Admin?

The Sales Navigator Admin CRM sync allows CRM Admins to:

  • Connect to an Online D365 Organization
  • Auto sync all seat holders in CRM
  • Set a Business Process Stage where Accounts and Leads from CRM will be imported to Sales Navigator
  • Allow Sales Navigator to size and group a won Opportunity
  • Enable Sales Navigator data to sync back to your CRM
  • Sales Navigator data items as Activities in CRM
  • CRM Data sync Statistics
  • Copy InMail Messages to CRM

Now let’s break down the Sales Navigator CRM Settings!

Sales Navigator Administration Settings

1. System Requirements:

  • Microsoft Dynamics Administrator User with CRM Admin security role
  • CRM Instances: Dynamics 2016 online or on premise and/or Dynamics 365 Online
  • Integration user account for CRM sync
  • LinkedIn Sales Navigator Enterprise Edition
  • Assumption that the LinkedIn Sales widget is successfully installed

2. Connect to CRM and then enter subdomain for the Dynamics 365 online instance, this will be followed by a request for credentials. The recommendation is to use a service account for these credentials. The reason is that when LinkedIn Activities (InMail, Messages etc.) are copied to Dynamics 365 these LinkedIn Activities are “Completed by” the CRM Admin for the Sales Navigator account versus the record Owner.

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3. Confirmation of Connection to Dynamics 365 and the date of the last sync with Dynamics 365.

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Below are the other configurable settings:

4. Auto Sync CRM allows Accounts and Leads to be automatically imported to Sales Navigator

5. Use Business Process Stage to import Accounts and Leads into Sales Navigator. The drop-down menu allows for five optionset values. The first is “Not Sure” the remaining four values are the Dynamic Out-of-the-Box business process stage names, 1-Qualify, 2- Develop, 3-Propose, 4-Close.

6. Storing the value for a won Opportunity allows Sales Navigator to size and identify the profile of deals. There are two available values for this option set, “Not Sure” and “Amount”

7. Sales Navigator syncs back to CRM. These data items become Activities in CRM. Below is a sample InMail message created in Sales Navigator with the copy to CRM feature enabled. The third view is this same message showing as an Activity item in Dynamics 365, how cool!

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8. Sales Navigator data items as Activities in CRM. Users can create LinkedIn messages while working in Dynamics 365.

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9. Sales Navigator Sync Statistics can be viewed by clicking on the View details link of the connected Dynamics instance. The table of CRM Data Sync Statistics shows stats for records the Accounts, Contacts and Leads entities.

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10. The Admin sub menu item “Seat Management” allows enabling of the CRM Sync feature for a Sales Navigator Seat (aka Dynamics 366 User).

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Pretty great stuff, huh? We hope this has provided relevant information about the Linkedin Sales Navigator from the CRM Administrator’s perspective. In review, we connected and configured Sales Navigator settings, showed the sync with CRM Activities, the CRM Data Sync Statistics and enabling CRM sync at the seat level. For more information about the LinkedIn Dynamics Sales Navigator see these tutorials.

Happy Dynamics 365’ing!

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PowerObjects- Bringing Focus to Dynamics CRM

5 Things We Learned at the Digital Transformation for the Modern Manufacturer Round Table

5 Key Points 300x225 5 Things We Learned at the Digital Transformation for the Modern Manufacturer Round Table

On February 15, PowerObjects met with industry professionals in the Bay Area to discuss the latest in business trends and innovative solutions. We acknowledged challenges in the industry today and explored how companies rise to the challenge to stay connected with customers and employees. Below are the five things we learned:

1. Customer Experience

It’s no secret that customers today are forcing companies to re-evaluate customer experience strategies. To thrive in today’s economy, successful businesses are re-focusing on superior service through an Omni-channel approach, including self-service capabilities, and empowering agents to surpass standard service levels and have informed and productive interactions with customers.

2. LinkedIn Sales Navigator

Companies are leveraging tools like LinkedIn Sales Navigator with Dynamics 365 for Sales to develop and cultivate customer relationships. LinkedIn Sales Navigator seamlessly integrates with Dynamics 365 and Office 365 to manage and analyze existing relationships while identifying potential opportunities. Watch LinkedIn Sales Navigator video here!

3. Artificial Intelligence (External)

Imagine your company taking a proactive approach to issues, instead of a reactive one. What if you reached out to a customer about correcting product failure before they even knew there was a problem? Artificial intelligence and Connected Field Services are giving companies a chance to predict and analyze products and services, and increase the overall customer experience.

4. Artificial Intelligence (Internal)

AI tools are reshaping the industry, both externally and internally. Tools like Customer Insights provide customer data in real-time with visibility to departments across the company. This allows these businesses to make better data-driven decisions. For example, AI tools deployed on a website or app can observe, learn, analyze and predict prospect behaviors for a sales team to focus effectively on leads based on these AI analytics.

5. Change Management

We learned that change management is not the easiest for companies to define yet one of the biggest challenges they face. It is important for companies to recognize change management is the people side of change. Even the best software implementations can fail if the change management plan is not well thought out (or not thought about at all – yikes). Addressing the impact to employee users helps companies get the most out of their digital transformation investment. PowerObjects employs change practitioners and certified trainers to guide users through Dynamics 365 for an overall successful transition.

For more on round table experience and industry discussion, check out our Digital Transformation PointDrive.

Subscribe to our blog to stay up to date with the latest news and trends with Dynamics 365!

Happy Dynamics 365’ing!

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PowerObjects- Bringing Focus to Dynamics CRM

Learn more about using Big Data Manager – importing data, notebooks and other useful things

In one of the previous posts on this blog (See How Easily You Can Copy Data Between Object Store and HDFS) we discussed some functionality enabled by a tool called Big Data Manager, based upon the distributed (Spark based) copy utility. Since then a lot of useful features have been added to Big Data Manager, and to share with the world, these are now recorded and published on YouTube.

The library consists of a number of videos with the following topics (video library is here):

  • Working with Archives
  • File Imports
  • Working with Remote Data
  • Importing Notebooks from GitHub

For some background, Big Data Manager is a utility that is included with Big Data Cloud Service, Big Data Cloud at Customer and soon with Big Data Appliance. It’s primary goal is to enable users to quickly achieve tasks like copying files, and publishing data via a Notebook interface. In this case, the interface is based on / leverages Zeppelin notebooks. The notebooks run on a node within the cluster and have direct access to the local data elements. As is shown in some of the videos, Big Data Manager enables easy file transport between Object Stores (incl. Oracle’s and Amazon’s) and HDFS. This transfer is based on ODCP, which leverages Apache Spark in the cluster to enable high volume and high performance file transfers. You can see more here: Free new tutorial: Quickly uploading files with Big Data Manager in Big Data Cloud Service

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3 Things About Machine Learning Every Marketer Needs to Know

20180117 bnr data nodes shop 351x200 3 Things About Machine Learning Every Marketer Needs to Know

TL;DR: Machine Learning 101: 3 Things Marketers Need to Know

Got data?

I bet you do.

Mountains of data, in fact. Terabytes of data. Libraries worth of data. With more streaming in every hour of every day.

We marketers love our data, but, let’s face it … we probably only use a fraction of the data we collect.

It’s not that we don’t want to use more of it. We do.

It would be fantastic, for example, to follow each and every customer around, to see everything they read, how long they read it for, where they clicked next. You might even want to drop a cookie on their computer and see all the other websites they went to. You could survey them, too, and send them personal messages on social media. Test when is the best time to send them messages, and which channel they respond to best.

Then, with all that wonderful knowledge, you could hole up in your office and design a complete soup-to-nuts marketing strategy just for them.

I’m not talking about something like account-based marketing, where your work is for one big target company. I’m talking about a totally personalized, hand-crafted marketing strategy and execution for every single possible prospect your company could have.

Just think of it: thousands of completely personalized marketing plans. Tens of thousands of personalized messages. Hundreds of thousands of hours poring over the data, studying exactly how each and every single prospect behaves.

That’d be great, right?

Well, if you had unlimited time and unlimited resources, maybe. If you never had to sleep, and had no family and no life … and the assurance that you’d live to be at least 312.

Otherwise … forget it.

Being able to focus that closely and to process every little bit of data we have about our prospects and customers is laughable. Delusional.

We are not machines.

At the most, we only have enough resources to segment our audiences. We have to create personas and buyers journeys based on our best guesses (informed by the data, of course).

But what if machines could do all that?

What if a well-trained algorithm could follow each one of your prospects around and could recommend the perfect piece of content and send it to them at the perfect time, in the channel they’d be most likely to respond to it in? And what if the algorithm could even predict the perfect time for your ace salesperson to finally give them a call?

That’s what machine learning can do.

Here’s what you need to know about it (at least for starters).

Machine learning is a subset of artificial intelligence.

At its simplest definition, machine learning is nothing more than “using data to answer questions.” Hat tip to thank Google’s superb video series on machine learning for that definition.

It’s a specific type ‒ or discipline, if you will ‒ of artificial intelligence. One of its strengths is that a machine learning algorithm’s accuracy can improve over time. It can “learn.” So. while a program that can play chess might be considered artificial intelligence, a program that can learn to play chess, and ping pong, and any other game, would be an example of machine learning.

More complicated machine learning systems are often called “deep learning.” So, for the game example, deep learning systems are set up to use multiple levels – called “neural nets” ‒ to do their processing.

Here’s a Venn diagram to help understand:

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Act-On Blog

3 Critical Things Sales Can Learn From IT

If you’re in sales, there are people in your organization you want to talk to, and others you may go out of your way to avoid. You might be excited to talk to the CMO — or not so excited — based on the leads you recently worked. You might avoid the people from finance who bother you with questions, but you might enjoy conversing with your comp plan administrator — which would make sense, since many of us have a fondness for the people who hand us our checks.

However, there’s one group of people you may never even consider when you’re thinking about discussions inside your company: the CIO and IT team. Yeah, they’re important when your laptop won’t work, but do they really have anything to say that can impact your performance as a salesperson?

Well, yeah. In this day and age, they do.

If your business is on top of technological developments, you may be the beneficiary of an assortment of game-changing technologies. It behooves you to know what’s coming, when, and how well your team is preparing for it.

Imagine that you’re a Formula 1 race driver, and the CIO is the crew chief who’s preparing your car to be faster that any others on the track. Few drivers would fail to engage their crews to find out the latest changes, the timing of those changes, or other things they should know. Yet sales professionals often seem to strap on new technology and blindly hit the road — and sometimes, they crash and burn.

What do you have to talk about with your technology people? Plenty.

The Infrastructure for Your Artificial Intelligence

Artificial intelligence is coming — not to replace you, but
to serve as an assistant to help you be the best salesperson you can be.

With AI, you don’t just flip the switch and start getting suggestions. AI
must be trained — quite literally — using a very large data set. From there, AI will need a system of storage for the data it generates and the data generated by transactions — in other words, unstructured data about sales performance.

As a salesperson, you should be interested in how this data is stored and managed, since a failure in that regard makes your organization effectively blind — and it turns AI into a liability instead of an asset.

Ask your CIO whether your company is investing in object-based storage. Object storage has the advantage of being limitlessly scalable, and it can integrate new nodes automatically into a single storage namespace.

That means that IT can provision capacity in response to demand rather than trying to predict storage needs and provision capacity that sits unused. The worst-case scenario is that IT fails to provision enough capacity and fails to record a portion of your critical data, which would mean that AI would have to work with a partial picture of the data as it tries to refine its suggestions. That’s a guarantee that AI will never be as intelligent as you need it to be to help close deals.

Suggestion: Get familiar with how well IT is planning to cope with the data tsunami. That is a good indicator of how effective emerging technology will be at elevating your sales game — and it might suggest that it’s time to look for opportunities at organizations with more technology foresight.

The Depth of Your Internet of Things Offering

While the IoT promises big benefits to buyers and sellers, it also requires an enormous amount of trust. Allowing a vendor to install systems that deliver a constant data stream about your business operations is not something to be agreed to lightly — it requires the vendor to have all of its policies nailed down, and to hold all of its employees to an extremely high degree of integrity. If you’re in sales, you have to
sell this relationship as part of the deal.

IT needs to think through data policies thoroughly, and it needs to make sure that activities triggered by data in an IoT relationship completely map to the business process. It’s not enough to send replacement parts automatically or schedule maintenance proactively. The behind-the-scenes activities around contracts, invoicing, commissions and quote generation need to be hooked into this system, too.

Suggestion: Talk to IT to see whether the background activities needed to deliver IoT are part of IT’s plans, and get a timeline for the complete integration of business processes into the IoT infrastructure.

You may be pleasantly surprised by a comprehensive plan that lays the groundwork for great customer experiences and lucrative, long-term customer lifecycles, and that is something you can sell with complete confidence. On the other hand, you may be chagrined to find an IoT infrastructure that’s only partially baked, which could result in sales that turn into contractual nightmares and angry buyers in the near future.

Can You Actually Analyze Your Data?

For all the excitement over the last five years about sales analytics, it’s still often a battle to put the right data sets together to find actionable insights. Data from disparate cloud applications may not be easy to use for a number of reasons. There might be API mismatches between cloud providers. Also, different sales support systems may not work together. Finally, the unmanaged deployment of cloud applications for sales and marketing can create silos where data can be hidden.

That means that complete analysis can require a lot of work in preparing the data before any numbers can be run. That will take IT time — time the team often doesn’t have, and waiting for IT could result in stale analysis that has less impact than it ought to have provided.

Suggestion: Find out from IT how connected your various data sources actually are. That will help you understand what you know and what you could know, and it will put you in a much better place to make suggestions about next steps for data integrations.

Also, learn from IT how new cloud-based applications deployed without any thought about integration impact analysis. That will help remind you that
the IT team should be part of any cloud application decision if you want to maximize data’s impact on sales results.
end enn 3 Critical Things Sales Can Learn From IT


Chris%20Bucholtz 3 Critical Things Sales Can Learn From ITChris Bucholtz has been an ECT News Network columnist since 2009. His focus is on CRM, sales and marketing software, and the interface between people and technology. A noted speaker and author, Chris has covered the CRM space for 10 years.
Email Chris.

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CRM Buyer

3 Critical Things Sales Can Learn From IT

If you’re in sales, there are people in your organization you want to talk to, and others you may go out of your way to avoid. You might be excited to talk to the CMO — or not so excited — based on the leads you recently worked. You might avoid the people from finance who bother you with questions, but you might enjoy conversing with your comp plan administrator — which would make sense, since many of us have a fondness for the people who hand us our checks.

However, there’s one group of people you may never even consider when you’re thinking about discussions inside your company: the CIO and IT team. Yeah, they’re important when your laptop won’t work, but do they really have anything to say that can impact your performance as a salesperson?

Well, yeah. In this day and age, they do.

If your business is on top of technological developments, you may be the beneficiary of an assortment of game-changing technologies. It behooves you to know what’s coming, when, and how well your team is preparing for it.

Imagine that you’re a Formula 1 race driver, and the CIO is the crew chief who’s preparing your car to be faster that any others on the track. Few drivers would fail to engage their crews to find out the latest changes, the timing of those changes, or other things they should know. Yet sales professionals often seem to strap on new technology and blindly hit the road — and sometimes, they crash and burn.

What do you have to talk about with your technology people? Plenty.

The Infrastructure for Your Artificial Intelligence

Artificial intelligence is coming — not to replace you, but
to serve as an assistant to help you be the best salesperson you can be.

With AI, you don’t just flip the switch and start getting suggestions. AI
must be trained — quite literally — using a very large data set. From there, AI will need a system of storage for the data it generates and the data generated by transactions — in other words, unstructured data about sales performance.

As a salesperson, you should be interested in how this data is stored and managed, since a failure in that regard makes your organization effectively blind — and it turns AI into a liability instead of an asset.

Ask your CIO whether your company is investing in object-based storage. Object storage has the advantage of being limitlessly scalable, and it can integrate new nodes automatically into a single storage namespace.

That means that IT can provision capacity in response to demand rather than trying to predict storage needs and provision capacity that sits unused. The worst-case scenario is that IT fails to provision enough capacity and fails to record a portion of your critical data, which would mean that AI would have to work with a partial picture of the data as it tries to refine its suggestions. That’s a guarantee that AI will never be as intelligent as you need it to be to help close deals.

Suggestion: Get familiar with how well IT is planning to cope with the data tsunami. That is a good indicator of how effective emerging technology will be at elevating your sales game — and it might suggest that it’s time to look for opportunities at organizations with more technology foresight.

The Depth of Your Internet of Things Offering

While the IoT promises big benefits to buyers and sellers, it also requires an enormous amount of trust. Allowing a vendor to install systems that deliver a constant data stream about your business operations is not something to be agreed to lightly — it requires the vendor to have all of its policies nailed down, and to hold all of its employees to an extremely high degree of integrity. If you’re in sales, you have to
sell this relationship as part of the deal.

IT needs to think through data policies thoroughly, and it needs to make sure that activities triggered by data in an IoT relationship completely map to the business process. It’s not enough to send replacement parts automatically or schedule maintenance proactively. The behind-the-scenes activities around contracts, invoicing, commissions and quote generation need to be hooked into this system, too.

Suggestion: Talk to IT to see whether the background activities needed to deliver IoT are part of IT’s plans, and get a timeline for the complete integration of business processes into the IoT infrastructure.

You may be pleasantly surprised by a comprehensive plan that lays the groundwork for great customer experiences and lucrative, long-term customer lifecycles, and that is something you can sell with complete confidence. On the other hand, you may be chagrined to find an IoT infrastructure that’s only partially baked, which could result in sales that turn into contractual nightmares and angry buyers in the near future.

Can You Actually Analyze Your Data?

For all the excitement over the last five years about sales analytics, it’s still often a battle to put the right data sets together to find actionable insights. Data from disparate cloud applications may not be easy to use for a number of reasons. There might be API mismatches between cloud providers. Also, different sales support systems may not work together. Finally, the unmanaged deployment of cloud applications for sales and marketing can create silos where data can be hidden.

That means that complete analysis can require a lot of work in preparing the data before any numbers can be run. That will take IT time — time the team often doesn’t have, and waiting for IT could result in stale analysis that has less impact than it ought to have provided.

Suggestion: Find out from IT how connected your various data sources actually are. That will help you understand what you know and what you could know, and it will put you in a much better place to make suggestions about next steps for data integrations.

Also, learn from IT how new cloud-based applications deployed without any thought about integration impact analysis. That will help remind you that
the IT team should be part of any cloud application decision if you want to maximize data’s impact on sales results.
end enn 3 Critical Things Sales Can Learn From IT


Chris%20Bucholtz 3 Critical Things Sales Can Learn From ITChris Bucholtz has been an ECT News Network columnist since 2009. His focus is on CRM, sales and marketing software, and the interface between people and technology. A noted speaker and author, Chris has covered the CRM space for 10 years.
Email Chris.

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5 Things Everyone Should Know about Mainframes

What comes to mind when you hear the word mainframe? If it’s a computer from the 1950s, you probably don’t know as much about mainframes as you could. Keep reading for five little-known mainframe facts.

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Whether or not you work with the mainframe, we’ve got 5 mainframe facts that everyone should know!

If you work in the mainframe industry or have a strong background in technology, these mainframe facts may not be little-known to you. But to the public at large, they are.

1. Mainframes are the Size of a Fridge

The mainframes that filled entire rooms went out of style decades ago.

Today’s mainframes are about the size of a refrigerator. That makes them somewhat larger than your average server, sure, and certainly bigger than your personal computer.

But a fridge is certainly smaller than the gigantic mainframes of old.

2. Mainframes Can Run Windows

You may know that mainframes can run Linux in addition to native mainframe operating systems, such as z/OS. But did you know mainframes support Microsoft Windows, too?

Well, OK – not all mainframes can run Windows. And they can’t run any version of Windows.

But Windows is supported on certain mainframes. That makes a lot of sense if you think about it. Mainframes are powerful machines that can be more cost-efficient to maintain than a data center’s worth of servers. If you can run Windows workloads on your mainframes in addition to Linux and z/OS, then you can use them to consolidate your entire data center.

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3. Mainframes Host about 70 Percent of the World’s Data

Ever wonder where all the big data you hear so much about actually lives?

In many cases, it’s on a mainframe. Mainframes store about 70 percent of the total data in the world.

If you think about which industries still rely heavily on mainframes, this makes sense. Banking, insurance, retail and the like are industries that produce a lot of data. They’re also ones that tend to be powered by mainframe computers.

4. COBOL Remains in High Demand

Industries that rely heavily on mainframes also depend on apps written in COBOL, the venerable mainframe programming language.

Almost no one learns COBOL these days. You’d be hard-pressed to find a college computer science program that includes instruction in it.

Yet the fact is that COBOL skills are still in demand. And precisely because younger COBOL programmers are in short supply, businesses that depend on COBOL are willing to pay top dollar for programmers who can provide COBOL expertise.

5. A Single Mainframe Equals Hundreds of Regular Servers

How many regular, x86-based servers does it take to equal the computing power of a mainframe? About 1,500 – if you’re talking about IBM’s System z10 mainframe, which was released in 2008.

That data is a little dated, but it still provides a sense of the enormous computing power housed in a single mainframe.

Conclusion

Now you know what modern mainframes really look like and can do – and how much they have changed since the days of the first mainframes.

The malevolent mainframes depicted in films like Alphaville never came to pass, but mainframes certainly have grown much smarter, leaner, meaner and more powerful over the decades

Learn more about the five key mainframe trends to watch in the coming year by reading about the results of our fourth annual survey report:  State of Mainframe for 2018

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