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Nov 06

We’re surrounded by data. It is data produced in both private and public sectors. It is data generated by individuals or machines. The variety of Big Data is large and growing rapidly across both internal and external sources and offer immense opportunities for those who will take advantage of it.

Variety-of-Big-Data-Sources-Kapow-Software-COND_SMBehind the firewall, Big Data is stored in databases, file systems, Hadoop frameworks, documents, archives and legacy on-premise applications for ERP, CRM, content management and more.  Externally, outside the firewall, it is available in cloud-based applications (like Salesforce, Marketo and Ariba), partner and supplier portals, public web like government websites or competitor websites, social networks and many more. External data on economic indicators, public finance, healthcare, regulatory compliance and more also play a central role in many Big Data use cases. Everyday consumers are creating Big Data across Facebook, Twitter, LinkedIn, blogs, reviews and forums, offering insights into their preferences and behaviors.

To add to this variety, each data source has different characteristics. Data can be structured, like machine data or sensor data, well organized in fields within a record or file or it can be unstructured, like social media data with no pre-defined data model. It can also be somewhere in the middle between structured and unstructured.  Some data sources will have APIs and others will not, requiring alternative methods in order to access and extract data.

The bottom line is that there is really no one “killer” data source. It is the unique combination of sources that you tailor to address your business needs that will be the “killer” data for your organization. The ever-expanding pool of data sources and types is becoming available and opening a whole new world of possibilities. Start taking advantage of it now, experiment with new sources, augment traditional sources, iterate and find the data gems that matter to your business!

 

Author: Hila Segal, Director of Product Marketing

Sep 18

What is the next big thing in the Apps space after mobile apps stores?

This was the big discussion point in this week Information Management DM Radio show where I participated together with the always inspiring DM Radio hosts Eric Kavanagh, BI analyst Cindi Howson from BI Scorecard, and two vendor specialists, John Callan of QlickView and Randal Hoff of FairCom.

Here are  a few of my takeaways from the discussion:

If you divide todays applications into a three classes: 1) large enterprise apps (ERP, CRM, etc.), 2) cloud apps (expense reporting, HR, etc.), and 3) the mobile apps popping up in iPhone and Android mobile apps stores, you will find that there is a 4th application need that is not addressed by any of the classes above.

Every company has its own environment of data sources, documents, applications and customized processes around them, so none of the standard apps will cut it. At the same time building specialized data-centric apps will, unless widely needed, be too expensive and take too much time with traditional IT (Internal or outsourced) resources.

I refer to this as the “Unmet Application Need”, applications too expensive to build with traditional methods given their business value, but also too company specific to ever make it into a mainstream app store.

We discussed how this market today is somewhat covered by BI vendors, like QlikView, but in many cases BI technologies still cannot access or deliver all the relevant data and/or perform automated action on the results. BI solutions are often only a half solution.

To meet the unmet application need, an application must be very easy to build at low cost and it must cover all the functions:

  • Access data (from a variety of internal and external sources)
  • Explore the data,
  • Select data for further action
  • Perform action on the selected data
  • Deliver data (write data to other systems or share with other participants)

Access and the delivery of data can be very challenging. I mentioned how Synthetic APIs can resolve this challenge with the ability to bi-directionally interface with applications without APIs as if they were normal APIs.

I also mentioned how agile development and distribution of lightweight enterprise data apps through enterprise app libraries can meet the ever changing need coming from the impatient business users.

We talked about how these kinds of solutions are priced. I said that contrary to large enterprise apps, where the ROI on a single app justifies the entire investment, for the lightweight and specialized apps, the ROI is in a platform that can quickly deliver multiple apps, and the combined business value of multiple apps will more than pay for the investment.

Finally we discussed what the future will bring. Several of us mentioned that we are only in the infancy for covering this market need, and awareness created by the Radio show today will help accelerate this huge potential market.

You can listen to the entire radio show here.

Comments are welcome at sandreasen@kapowsoftware.com

Stefan Andreasen

Aug 09

Jettsetter 1Booking our hotels and flights online has never been easier and now more than ever as consumers we are empowered with information that helps us find the best deals. Good news for the consumers but for the on-line travel players it means a very competitive landscape. It means prices must be constantly adjusted and optimized in order to maintain and grow market share and always be one step ahead of the competition.

Jetsetter is in the business of luxury travel focusing on flash sales. Their members have a short period of time to buy a luxury travel deal. They differentiate on price and how they merchandize their offerings. When and how they price they offers is extremely critical for their success especially since they saw a lot of competition come into the space with new players pop up weekly. They needed  detailed market intelligence about what was being sold and at what prices at any given time in order to build a more detailed and precise pricing and merchandizing strategy.

Kapow was brought in to monitor competitors’ offers on the Web. This gave Jetsetter the intelligence to know when and how much to price their hotels offers. This fended off a lot of the their competitors, who eventually went out of business. Kapow gave them a strong advantage to rapidly access this intelligence and quickly scale as new competition emerged. By the second year, they pivoted their business and moved into the full price arena and competed with players such as Travelocity and Expedia.

As Shaun Stewart, Vice President  Sales and Operations at Jetsetter explains:

“Kapow Software provided us with a leg up in an industry where we had access to all competitors price points. It gave us intelligence to figure out how to merchandize and be more strategic about everything we sold.”

In a short span, Jetsetter has emerged as a premier player in the luxury travel space. They were acquired by the TripAdvisor, the leading travel review site in April 2013. Jetsetter 2

To learn more about the efficiencies and revenue gains this Kapow customer was able to realize by closely monitoring their competitors’ prices, view the customer testimonial on our website.

Authored by: Hila Segal, Director of Product Marketing

Aug 06

Earlier this year I penned a blog about the ‘Unknowns’ of Big Data Integration.  The focal point of the piece was the need for businesses to become more situationally aware by quickly harnessing data from a variety of sources to try to prepare for a ‘Black Swan’ event in the course of their business cycle(s).

Last week, Kapow announced that we would join forces with Kofax to lead the industry in making data more integrated and actionable in the enterprise.  The immediate alignment of our companies and the scale of the Kofax organization have the potential to create a new disruptive force in the Big Data Integration sector.

Over the years, we (at Kapow) have always championed the “TIME TO VALUE” (TTV) metric as the real justification for making economic business decisions.  The timing to join forces with Kofax will accelerate the integrated data deliverables to our customers and the larger Kofax family of customers.

The past 3 ½ years as CEO of Kapow provided me with a great opportunity to work with incredible people (our family) in an effort to deliver the best product and service to our customers.  In turn, our customers have been extraordinary in their support of Kapow and that was clearly demonstrated at our first ever user summit this past March.

I look forward to an unparalleled growth period for Kapow as part of the Kofax team with access to Kofax’s extensive resources, financial strength and global presence.  The best of times lie ahead as we continue to revolutionize the way data, coming from a wide variety of sources, is used in the enterprise to drive the business forward with greater precision, agility and affordability.

Thank you all for your support over the years and for your continued support for many years to come.

Authored by: John Yapaola, CEO

Jul 30

A lot of the discussion around Big Data often centers on internal transaction data available in CRM, ERP or other cloud-based enterprise applications. But by doing that organizations are taking a risk at missing the bigger picture. While these are important data sets for any organization it’s the combination of this information with external data sets that will provide a 360 degree view of the business. Here are other types of data you should be monitoring to discover critical information about your business, customers and competitive landscape:

  • User-generated data.

Your customers are sharing information about their experience with your brand, what they like and don’t like about your product, how it compares to the competition and many other insights that can be used for identifying new sales opportunities, planning campaigns, designing targeted promotions or guiding product development. This information is available in social media, blogs, customer reviews or discussions on user forums. Combining all this data with call center records and information from other back-office systems can help you identify trends, have better predictions and improve the way you engage with you customers.

  • Public data.

Public information made available by federal, state and local agencies can be used to support business operations in human resources, compliance, financial planning, etc. Information from courthouse websites and other state portals can be used for background checks and professional license verifications. Other use cases include monitoring compliance regulation requirements, bill and legislation tracking, or in healthcare obtaining data on Medicare laws and which drugs are allowed per state.

  • Competitor data.

Information about your competitors is now widely available by monitoring their websites, on-line prices, press releases, events they participate in, open positions or new hires. This data allows you to better evaluate the competition, monitor their strategic moves, identify unique market opportunities and take action accordingly. As a retailer for example, correlate this data with order transaction history and inventory levels to design and implement a more dynamic pricing strategy to win over your competition and grow the business.

  • Partner data.

Across your ecosystem, you have daily interactions with your partners, suppliers, vendors and distributors. As part of these interactions you are exchanging data about products, prices, payments, commissions, shipments and other data sets that are critical for your business. Beyond the data exchange, intelligence can be gleaned by identifying inefficiencies, delays, gaps and other insights that can help improve and streamline partner interactions.

To learn more about how you can start using all this wealth of available information join me on a 30-minute webinar next week, August 6 at 8am PST. We’ll be sharing real-world examples of how this data can be put to work and quickly turned actionable to drive results for your organization. http://bit.ly/119JG1f

Authored by: Hila Segal, Director of Product Marketing

Jul 18

How many times do you find yourself copying and pasting information from a webpage to an email or an excel spreadsheet and repeating it for different data sets? How efficient is that? Imagine doing it over and over again, capturing information, copying time sensitive data  from your partner ecosystem into your internal systems in order to make critical business decisions.

This has been the reality for PITT OHIO, a premier US-based regional transportation provider. Teams of employees were spending hours copying information about shipment statuses, delivery times and paid invoices interacting with various internal and external applications to complete daily customer service and credit and collection operations. They were not only spending time better spent on activities that might grow the business but they were also lacking agility required to be competitive in this industry where margins are laser thin.

PITT OHIO, like many other companies in logistics and in other verticals, are interacting with a vibrant and dynamic business ecosystem of partners, suppliers, vendors and customers. They needed a more efficient way to exchange data across their supply chain ecosystem without relying on costly, error-prone manual efforts.

As Darren Klaum, Director of Business Systems explains:

“Our Customer Service Representatives were maintaining a paper-based system to provide the 2-hour SLAs (service-level agreement) our premium customers needed. It was nearly a full-time job to support just one of our key accounts.  Kapow Enterprise Platform handles what our users were doing, automatically, more consistently and more accurately. We’re seeing a 95% reduction in manual effort.”  Darren Klaum

In the logistics and transportation industry efficiency is a key competitive advantage as it can boost margins and enable companies to win new business faster. The results for PITT OHIO are significant. Revenues increased by decreasing aged receivables, costs decreased by saving over 30 man hours a week, automating 100% of routine activities and improving productivity by 90%.

To learn more about the efficiencies and revenue gains this Kapow customer was able to realize through integrating and automating the data exchange across its supply chain, view the customer testimonial or watch the on-demand webinar.

Authored by: Hila Segal, Director, Product Marketing

Jun 25

Last week I participated in a Big Data Insight panel at the monthly Technology Executive Networking Group (TENG) in Dallas and the discussion was lively among the 50+ attendees. What I learned from the discussion and the great questions from the audience is that there still seems to be a lot of confusion about what Big Data is and how different it is from “traditional” Data.

I started with an example that for me describes “what is Big Data”. Think about buying a vacation. You need hotel, rental car, airline ticket, theater tickets, etc. In the past you called travel agents, explained what you wanted and they assembled your vacation for you and you bought it. Today you do this in a completely new way. You search for places to go, then you check the weather pattern for that time of year, look at hotel ratings, shop for flights, bid on a rental car, and you do this over a period of time to check if prices change before you make your purchase online with a credit card. This is Big Data and this resonated very well with the audience.

Among my talking points about what Big Data is, I realized I was breaking some perceived myths about the definition of Big Data:

  1. Big Data is about taking large volumes of data and processing it in Hadoop. In reality many Big Data initiatives will not reach the data volumes that require processing in Hadoop. Smaller data sets extracted from multiple sources can be as game changing when used to answer business questions.
  2. Big Data is about performing analytics on data. Yes data exploration and analytics is a big part of Big Data initiatives, but it must be tied to performing an action based on the results. Too many analytic solutions leave you with a report or data visualization without giving you the ability to change a business process or create new records in another system based on the data.
  3. Big Data relates primarily to unstructured Data. Key new sources that became available like social data might be unstructured in nature but to make data actionable its needs to be as structured and factual as possible.

So, what is different from data as we used to know it and Big Data? One of the Panelists, Chris Boult, Vice President of Infrastructure & Data Services, Sabre Holdings, said it perfectly: “Traditionally we used to examine our transaction database to create business insight and derive new business initiatives. Now we look for the data that leads to the transaction data, for example how does people search and book airline tickets.” This is the essence of Big Data – leveraging data sets from internal and external sources to extract insights that you can act on.

Big Data is hard though. As data generating and data driven applications spread throughout companies and their business ecosystem, getting and distributing data has become the biggest integration nightmare ever. The explosion of data sources and the fact that the half-life of data (the period in which data has business value) has become shorter requires a different approach to dealing with data. An approach that enables organizations to:

  1. Quickly discover, acquire and combine data from internal and external sources
  2. Intuitively explore the data to figure out what to do with it
  3. Take data-driven action such as perform a business transaction or dynamically change prices based on competitors’ prices
  4. Create and package steps 1-3 into a smart business application that can be used directly by business consumers, and – this is important – do that in a matter of hours or days, rather than weeks or months

At the end of the session the panel was asked, “What is the biggest mistake you have seen around Big Data?” My clear answer was, “The biggest mistake it not to pursue Big Data”. Only by stepping over the line of how you used to work with data and get going with Big Data, will your company prosper.

A big thank you to BravoTECH and co-founder Andrew Jackson for hosting a successful event.

Comments are welcome to  Stefan.Andreasen@kapowsoftware.com

Authored by Stefan Andreasen, Founder and CTO at Kapow Software.

 

Jun 18

While traversing through my spreadsheets, it was startling to realize the amount of company data that I have created in Excel over the years. Some of this data is very valuable but resides in the silo of my outpost world. Excel, for me, represents an automation of information. It’s a way to move disparate information into a commonplace, where I can manipulate it. Excel is a passive documentation tool that allows me to play ‘what if’ scenarios on data sets and send the spreadsheet to others to review. But unless you understand the ‘construct’ of that particular Excel model, much time is wasted trying to just understand assumptions. A relic product from the 1980’s still widely used, but why?

Let’s look at an analogy from the gaming world. In older versions of video games (from the 80’s), gameplay was represented as a competitive (1-vs-1), time-restricted engagement, where the winner defeats an opponent within the pre-determined rules of the game. Modern game-play evolved and has less to do with winning and losing and more to do with in-game decisions, which drive different possible outcomes. Key to game play is the constant monitoring and situational awareness from a variety of events that are random, frequent and can morph into more complex scenarios.

Excel ImageExcel was released by Microsoft in 1985. Some 30+ years later business and IT continue to default to Excel, assembling disparate information into spreadsheets creating island data repositories because no one has developed the next generation ‘game’. Just like in games, where proficiency and excellence is a function of continuous game play, businesses must empower workers with actionable information that will enable real-time (in-game) decision making. In the world of Big Data and a business climate of Unknown Unknowns, where business fragility is on the rise, the need to be situationally aware of market conditions and competitors requires a different approach.

An approach that enables organizations to monitor, acquire and act on the data in an agile way without it being locked in static Excel files, so additional data sets can be dynamically added and users can interact with the data in an intuitive graphical interface. Users should be able to build their data proficiency through experimentation, allowing them to test hypothesis and discover new insights with simple access to critical data. And by users, I don’t mean the PHDs and data scientists but employees in sales, marketing, customer service, finance, procurement and supply chain – those who are responsible for the growth of the business.

Excel was originally created to make it easier for people to organize data. This was when data was mostly internal coming from very well defined structured sources. With 90% of the data created being unstructured and 168 billion emails sent every minute, it’s time for the next evolution of SW that puts data with all its volume, variety and velocity in the hands of users. More interaction with data increases acuity and hones decisioning.

Click to see this approach in action supporting sales intelligence or social media monitoring.

Authored by John Yapaola, CEO of Kapow Software

Jun 05

Imagine you are in downtown Manhattan trying to catch a taxi at 5pm. Not an easy task. You might be standing there for some time. Well, by using the Click a Taxi mobile application you might be able to get out of there much quicker….

This application allows you to book a taxi wherever you are without even knowing the name of the local taxi company. Click A Taxi is able to fulfill that promise by building a global taxi network of 300,000 taxis across 50 countries and 5000 cities. If you think about the typical taxi company, API is not a common term for them. To execute on their vision, Click a Taxi had to build integrations with taxi companies even when APIs were not available. With Kapow, Click A Taxi is able to build Synthetic APIs and complete integrations with a taxi booking partner within 1.5 days. ClickATaxi

The scale and agility has been game changing for this innovative company and critical for their rapid global expansion. As Søren Halskov Nissen, CEO of Click A Taxi explains:

“Without Kapow technology, we couldn’t have expanded into this many cities so fast. Our average partner integration now takes less than two days to complete. Kapow’s Big Data integration platform has helped us surpass more than 100,000 bookings a month and has grown our business much more quickly. It is also a much smoother, stress-free process using Kapow.”

Click A Taxi have recently been recognized as a winner of The Next Web’s 2013 Danish Startup Awards as the Best E-commerce Platform. We’re proud to help them drive award-winning innovation.

Information critical to the business is distributed across the enterprise ecosystem and like Click A Taxi, companies are required to interface with a growing number of partners, suppliers and other business stakeholders for their core business operations. To learn more about how this customer built intelligence into its partner ecosystem through rapid integration, view the on-line testimonial.

Authored by: Hila Segal, Director of Product Marketing

May 15

Everyone’s talking about Big Data. About the great volume, variety and velocity of the data as well as the value it can create to those organizations that fully leverage Big Data. But how many companies today are really taking full advantage of Big Data in a meaningful way?

Survey Image 1To find out, we at Kapow have commissioned a market survey to gauge attitudes toward Big Data initiatives among business and IT professionals, gaining insight into the perceived challenges, benefits and what is required to be successful with Big Data initiatives. While more than 85% of both business and IT respondents agree that the value is in the ability to foster a data-driven culture and make intelligent business decisions – only 23% rate their Big Data initiatives as successful.

So why is the gap so big?  Among the key perceived barriers are concerns about having the right skills, time it takes to derive real value from Big Data and the ability to effectively leverage variety of data sources.  The wish list of what Big Data solutions should provide include data integration from multiple sources, automation of data collection tasks, shortening the time to put data to work and making relevant data more consumable for workers without relying on data scientists. Unfortunately over 50% of respondents say their Big Data solutions today are not effective in addressing these requirements. Survey Image 2

While manual data aggregation is still widely common among over 80% of the respondents, 85% believe Big Data strategies should be user-centric so that Big Data insights can be easily consumable by business consumers in sales, marketing, customer care and finance – to make more agile decisions. These solutions will remove barriers related to talent, time and resources and will make Big Data readily accessible, affordable and actionable across the organization.

The result is that customer service reps are better equipped with relevant information from a variety of internal and external sources to reduce the call time and provide better service experience. Sales executives spend less time finding information about their prospects and marketing managers know more about their competition in real-time.

Put data to work for you!

Click here to view whitepaper and infographic.

Authored by: Hila Segal, Director, Product Marketing

 

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