Note – This is a post authored by Rob Rowe, Sr. Manager, MDM Product Marketing, Software AG. I just helped in co-authoring the part about taming big data since I have already written on the topic before.

We’ve all heard about big data and there are numerous definitions of it. Suffice to say, it’s a lot of data from both inside the organization (e.g. ERP, CRM, application logs, etc) and outside the organization (e.g. Twitter, Facebook, and other social media, videos, news feeds, mobile apps, smart meters or other devices, etc). Whatever big data means to you, the real challenge is harnessing all this data and making sense out of it to provide real business value.

Enterprises today focus on application integration as data grows at an explosive rate everywhere. In order to tame such big data growth, traditional integration techniques may need to be complemented with newer design patterns such as in-memory data management platforms. An earlier blog post on this details this approach using three use cases.

With the explosion of data everywhere, Master Data Management (MDM) also becomes a critical point of observation. However, MDM works hand-in-hand with Big Data and is enabled by integration. There are two sides of this which we will explain. The first is using master data to provide “grounding” for the data, such as positively identifying the source of a social media stream. So for example, someone writes on Facebook that they are unsatisfied with a certain product. As it happens, it is YOUR product!  But, identifying this requires a Master Product repository. You also want to know who this person is so that you can investigate and rectify the situation.  This requires a Customer Master. You want to maintain brand integrity and customer satisfaction levels. So if this person is one of your customers, and they “liked” you on Facebook, perhaps to win a prize or receive a discount, then you not only have their “standard” customer profile information, you also have the supplemental information of their Facebook name. They are already in your database and you know who they are. You can contact them and resolve the issue, ideally in real-time, before your customer loyalty or your brand reputation is tarnished.

The second side of this is that big data can provide valuable information which can supplement the data that you’re already mastering. Yes, it works both ways. For example, let’s take a utility company that is mastering the location data of their smart meters, as well as the product data associated with the meters, transformers, and all the other important assets of the business. From the (big) data, integrated with the real-time analysis tools, it is discovered that a smart meter is no longer reporting its data. Because you are mastering location data, you know where this meter is, you know what type of meter it is, and you know what customer is affected. The call logs can verify whether the customer has already called in a loss of service. Having all this data allow the utility company to dispatch someone close to the troubles location, investigate the problem, and resolve it quickly, perhaps even before the resident comes home from work.

So as you can see, big data, master data, and integration together can produce valuable insight and real business value. Want to know more? Attend our webinar entitled “Taming Big Data and MDM with Integration” on May 15, 2013. You can register at http://www.softwareag.com/corporate/res/webinars/innovation/default.asp

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Here’s a summary of the highlights:

The new ARIS release provides social collaboration capabilities that leverage the wisdom of the crowd for process improvement and increased awareness and buy-in for your process excellence initiative.  Smarter analysis functions get more out of your existing process content and most notably  impact analysis has made a huge step forward. You want to see which IT system is supporting which process? This analysis is done in seconds and beautifully visualized. Cutting-edge user experience and self-explaining process visualizations will increase the process improvement footprint in your organization while central configuration, document management and license management/distribution will lower administration efforts. The new scalable private cloud architecture combines performance with maximum data security.

Process publication without the need to read a process model

ARIS Connect is a new product in the ARIS portfolio.  ARIS Connect generates process publication without the need to read an actual process model. With this anybody is now able to understand and improve processes.

Process modeling and social collaboration in ARIS Connect

In a process publication portal you can directly modify an existing process or design a new one. Need help? No problem, just start social collaborating to make the process better.

BPMN model in ARIS Architect

BPMN 2.0 is a first-class citizen in the new ARIS release. You can simulate, analyze, publish and export BPMN models.

Smart ad-hoc analysis in ARIS Architect

Let’s say you want to know which functions in a process are perfromed by Maria Lopez? Just use the ad-hoc analysis to find the answers in only a few seconds. Use the results to create output screens to share them in your organization.

Easy calculations and attribute maintenance

Spreadsheet is a new model type which looks simple but has a lot of power. Just drag and drop objects/processes on the grid and you can easily do calculations as you know it from Excel. If you change an attribute, it will also be changed in the models. You can directly create an ARIS MashZone dashboard on top of the grid.

I have been working with ARIS for more than 13 years now and I must say that this is by far the biggest step forward in ARIS history. So are you interested in finding out more?

- Visit our ARIS 9 website

- Attend our webinar series to see ARIS 9 in action

- Follow our ARIS blog on ARIS Community and read our post series focusing on the hottest ARIS features in the coming weeks.

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IMDM enables real-time processing of transactions to detect fraud by maintaining all data in-memory. This results in faster detection of fraud and faster action to eliminate fraud losses. IMDM easily integrates with different applications to manage several types of telecom fraud:

1. Toll Fraud or Compromised PBX/Voicemail Systems Fraud

Compromising a PBX/Voicemail system to call toll numbers is the top fraud loss category. Within minutes operators can lose hundreds of thousands of dollars by calling toll numbers that charge $5/minute or higher. IMDM allows analyzing call detail records (CDRs) in real time using a dynamic set of rules to minimize & eliminate this type of fraud.

2. Bypass Fraud

Bypass fraud manifests many different forms but essentially involves unauthorized traffic in an operator’s network. This can be difficult to detect but IMDM makes it easier by maintaining all real-time transactions in-memory to review the source of the transactions, the destination number, the cost of the call, etc. IMDM holds streaming data in-memory to prevent a denial-of-service attack that could have led to an operator’s network becoming totally unresponsive to their customers.

3. Credit Card Fraud

Telecom organizations get hit with several different kinds of credit card fraud related to charge backs, returned checks, card holder not present, etc. IMDM enables maintaining real-time and historical transactions in-memory to quickly analyze the root cause and prevent fraud. Leading credit card organizations are already using IMDM solutions to manage their fraud.

What’s been the impact of fraud on your organization? Could IMDM solutions be an option for you?

(This blog was originally written on the Real-Time Big Data Blog and has been republished on Reality Check)

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Whether you’re focused on improving business processes and integration, or looking for new strategies around Big Data or transactions, this one global event will inspire you with groundbreaking innovation and insights.

• Learn how you can transform your organization into a Digital Enterprise that acts faster in ever-changing market

• Discover how to capitalize on mobile, social, cloud and big data while leveraging your current IT investments

• Visit product-specific Innovation Worlds on ARIS, webMethods, Terracotta and Adabas-Natural

• Engage with hundreds of peers, valued industry experts, and inspiring digital leaders

This one international event is for everyone interested in IT-driven innovation centered around delivering business value and solutions people never thought possible. Register today and take advantage of the early bird savings.

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For those of you not familiar with Electrolux, it is a Swedish company with 58,000 employees in over 60 countries. They manufacture and sell cookers, ovens, dishwashers, laundry products, vacuum cleaners, air conditioners and products of professional use. The company has started to make the move from a manufacturing organization to a consumer-driven business which, as you can imagine, comes with its own set of challenges. The biggest challenge was to break up organizational silos to improve customer-facing processes in an end-to-end manner. Obviously you always step into someone’s territory if you improve processes end-to-end. For this, it was key to have the leadership team behind the project. This was exactly the case at Electrolux. Process improvement was seen more as a management discipline than technology. Management set the objective to make processes transparent and to simplify, improve, and manage them.

So for phase 1,

Jean started the project (initiated by a new ERP implementation) by creating a BPM framework defining governance, roles, communication, and methodology based on the C-level objective to simplify processes. With this, the process improvement initiative was nicely integrated in the corporate strategy and thus became a high priority in the organization. Because of this, teams directly approached the BPM competence center to support the mapping of as-is processes and to improve them. The competence center checked first which teams are interested in process improvement and chose them to participate first. Early results were used to convince the other departments to participate. After the collaborative process design/improvement exercise, done collaboratively by business and IT, the processes were implemented in an ERP system.

Phase 1 benefits for business…

- Processes gave visibility to the business and influenced other functions/silos transparent

- Now decision making is based on the full understanding of end-to-end processes

and for IT:

- Improved translation from business requirements

- Now ERP implementation is based on improved processes.

During phase 2,

the objective was to achieve higher process visibility. Electrolux wanted to see what was happening across the entire distribution network in real-time. They wanted to know: How many orders are coming in? Which orders are coming through which distribution center? Where are the orders coming from? Answers should be provided in real-time and filtered by product line.

The BPM team wanted to analyze trends so problems could be fixed before the customer discovered that there was an issue. Which is why having real-time information and analytics were a key part of their process improvement strategy. They could no longer wait for a daily shipment report; it was critical to identify problems in real-time and have the order corrected immediately. Understanding these requests created immense benefits.

To get the supply chain visibility they need, Electrolux chose iKnow from Software AG to define metrics and monitor KPIs gathered from the ERP system. iKnow at Electrolux is today providing visibility for:

Phase 2 benefits:

- Real-time information vs. a day old BI report

- Inventory issues found before consumers discover them

- Identify and correct process bottlenecks before the consumer is affected

- Helping the business to deal with exceptions instead of dealing with everything

During this initiative, Electrolux learned that by defining to-be processes before the ERP implementation and enriching the operational system with iKnow Process Intelligence, Electrolux got a supply chain solution that improves processes and provides actionable information. Jean also mentioned how important an appealing visualization of data is. Working with data is just more fun if it looks good. It also helps to use the dashboards to turn real-time data into real-time information and with this, turn them into real-time action. iKnow comes with very nice dashboards that really want to make you play/work with it. You find example dashboards for service level agreements, inventory management, and others here.

One of the key pillars of success for Electrolux was the collaboration between business and IT which isn’t always easy because they speak different languages and use different tools. But they realized they had the same objectives and by achieving end-to-end process visibility they are able to  move from a reactive to a predictive management approach. Having consistent objectives for business and IT helped a lot in getting both parties to work together and drive results.

In the next phase, Electrolux will move from the order-to-fulfillment process to order-to-cash, covering multiple channels. iKnow will be used for the BPM team as a follow-up step to process mapping.

A big thank you to Jean Lastowka for the great presentation! Me and the entire audience were really impressed with what the  Electrolux team was able to achieve in just one year.

You find further reviews of Gartner BPM Summit sessions in Sandy Kemsley’s blog: http://www.column2.com/

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Business Intelligence is a thing of the past. Companies used to look at their past performance and understand their mistakes or achievements. In today’s world of tweets and posts, even news agencies can’t keep up with the speed at which information is traveling across the world. Enterprises need to be extremely proactive rather than being reactive. So, a few years ago, the concept of Social Business Intelligence was introduced. There is abundant information available in all the petabytes and zetabytes of social feeds across all social networks. The ability to single out the right channel, to kill unnecessary noise and to make sense of the remaining social information into actionable metrics is called Social Business Intelligence. For example, a retail company monitoring specific social feeds of its consumers can understand that they actually prefer its newly introduced product in red more than blue. Using this data, it can instantaneously prepare its supply chain to ship its next batch of products in red rather than blue.

However, there are inherent challenges with gathering such social data. To start with, social data is not structured. Consider a tweet such as this – “Love the fit of #Gap’s new #slimfit #jeans. Zipper not smooth”. How do you associate a metric with such a tweet? Is it a positive tweet or a negative tweet? How do we classify this tweet to make predictive intelligence from this? To address this, we have many tools out there that perform “Sentiment Analysis” on such social data. This type of analysis assigns weights and scores to social data and makes the data more meaningful for Social Business Intelligence dashboards.

There has also been another trend in the last couple of years – an increase in adoption of social media platforms within enterprises. This can span just within employees or even with customers and partners. These tools help in keeping collaborative teams closer and well-informed. And, this is where I will introduce Social Business Intelligence 2.0. The social feeds have grown to gargantuan proportions that they have created silos of Big Data by themselves. Next, the information in such social data is not useful freestanding on its own. They need to be cross-referenced with other data stores in the enterprise such as Product Master, Customer Master, Pricing database, Support Center application etc. This is the way that coherent information is created from such chaos.

Let me give you an example of such a Social Business Intelligence 2.0 scenario. Customer X logs in a support ticket about a system failure in one of their servers. The support system instantly posts a note about that ticket into the corporate social feed under the support channel. Since a few stakeholders such as the Account Manager, Systems Engineer and on-site consultant have subscribed to this specific customer’s posts, they get notifications about the post and are aware that the customer has an issue. They can immediately call up the customer expressing their interest in addressing the issue ASAP. This increases the level of customer satisfaction as well. But, what has also happened behind the scenes is that there were three other similar issues (with the same component) raised by three different customers in the past 1 week. But, those were not trouble tickets but just social posts in support forums. The correlation is made between the various social posts and a social notification is sent out to the relevant R&D team automatically. Members of that team see that post, understand the problem and release a fix immediately addressing the issue. Next, an automatic notification goes to each of those affected customers’ technical contacts indicating the availability of this fix, which addresses their problem.

Yes, I know that sounds like a fairy tale and hardly ever happens that way in any company. But, that is not wholly true. There are quite a lot of companies that are leading the charge on such initiatives and making great strides in bringing such solutions to reality. What I want you to focus on is the underlying technology to make this happen. First, yes, you need a social platform that can primarily connect everyone together. Also, the APIs of this social platform should be open enough that it can be called from other applications or from the integration platform. Second, you will need a correlation engine or a Complex Event Processing (CEP) engine that can associate disjoint data and identify patterns in them. The third most critical thing you need in such an environment is an integration backbone or an Enterprise Service Bus (ESB). This will be the glue that connects all of the moving parts in this environment together.

An ESB within a collaborative enterprise helps in enabling Social Business Intelligence 2.0 by –

• Understand and parse structured / unstructured data from various social sources
• Integrate social data from various sources into a correlation engine or a sentiment analysis engine
• Connect up with various Master data sources and lookup databases within the enterprise. This will help in classifying social data into relevant taxonomies.
• Integrate support systems, R&D systems etc with social data streams so that automatic posts can be sent into appropriate channels based on incoming / inferred data
• Pump all metrics and social analytics data into dashboards to create real-time actionable views for relevant stakeholders

An ESB can also leverage complementary technology such as in-memory management solutions to process Big Data effectively. Social Business Intelligence 2.0 is already here. I urge you to start considering your integration backbone / ESB as an effective platform to launch it within your enterprise today.

Until next time, Ciao!

The post Social Business Intelligence 2.0: Driven by Integration appeared first on Reality Check.

In my role, I have the privilege of meeting with exceptionally bright customers to hear what they are doing. Most of these customers tell me that they are witnessing the effects of the nexus of 4 forces – Mobile, Social, Cloud and Big Data. A lot has been written about the nexus of the four forces – Mobile, Social, Big Data, and cloud. But, I think more importantly it’s not just that the forces exist, but what are these combined forces creating?

From what our customers are seeing, we believe these forces are creating proliferation of 3 key assets: Data, Services and Devices. It is this proliferation that is pushing integration to be the key focus for all new applications.

Data Proliferation

Big Data is everywhere and the newest and probably hottest area in the marketplace but integrating this big data is key to deriving business value. Data integration can be as “simple” as creating a single view of the customer – basically creating a single logical record of the customer data across the enterprise so that all interactions with the customer are consistent, and all relevant data is considered as part of that interaction. As one of our customers who is in the pediatric healthcare business put it, this single view isn’t a nice to have but it saves lives by ensuring all drug interactions are known and factored in from their pharmaceutical, surgical and ER systems. But, data integration can be much more complex, involving statistical pattern matching, algorithmic correlation and producing a model that predicts whether a particular transaction is safe or fraudulent. No matter what the application, if you are talking about data proliferation you probably need some form of integration to bring this all together.

Services Proliferation

My prior blog entry on “Big Services”  describes this area, but consider a relatively simple transaction of shipping a product from your favorite online retail site – there is probably dozens of services that need to be integrated together to provide a seamless experience – Customer data from one or more services, product data from another service, logistics data from the warehouse, preference list from a predictive analytics service, shipping time from the shipping service, credit verification from the card issuer, etc. This is a very simplistic view since products usually come from one or more partners, and the logistics and product availability is derived from warehouses across the globe. Net net, though, is that integration of these systems is key to ensuring that the customer has a great experience.

Device Proliferation

Much has been said about Bring your own Device (BYOD) and the need to have applications that address iOS, Android, Windows, web, and the multitude of screen sizes, but the real device proliferation is around the “Internet of Things”. Integration of the information these devices create is a key enablers to new applications. Consider another customer of ours who is in the recycling business. They integrate GPS data with telephony data, and create an application where customers can view where the recycling truck is and alert the customer when their recycling container has been picked up via a text message. Again, it is the integration that makes this application interesting and compelling.

What This Means for You

Integration is the application, and it is only through integration of existing assets that new compelling applications can be created that provide differentiated value. You need to have a plan and partner that takes the proliferation of data, devices and services into account and allows innovation through integration, only then will you truly have applications that take your business to the next level. Conversely. I challenge you to find the application that has no integration!

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For example, we have customers embedding OneData portlets in some of their applications. This provides read-only access to data, but it’s just like being there. Actually it IS being there, with anonymous user privileges.

We have other customers granting permissions to view only specific data for the intended user through direct links into OneData Objects. Yes, you can actually filter this data which might be useful for sensitive data, or to comply with privacy or other regulatory mandates.

Some of our customers are accessing data in the field using their iPads. This becomes quite handy when you’re on the go and can’t wait until you get to a computer to obtain needed information.

We even have customers who have placed OneData in the cloud, providing data and services to THEIR customers!

As companies scale up, they find that they may need additional database licenses, which can quickly add to their TCO. But we have a solution. Using Terracotta, you can load your MDM repository contents into memory. Not only do you get better performance, but you save the cost of additional database licenses. You only need a small database to persist this data.

To summarize, we have portlets to access mastered data, direct database links to specific data, iPad access, cloud access and in-memory access to trusted data.

In addition, OneData has a unique capability to centrally master data in the enterprise which is external to it’s own repository! It can manage this data as if it were it’s own. Really!

So when I started thinking about the many places where master data can be accessed and managed, I came up with the idea that webMethods OneData is the trusted data everywhere MDM platform. And there you have it.

The post webMethods OneData – The Trusted Data Everywhere MDM Platform appeared first on Reality Check.

Of course, technology is a critical component to leveraging the power of the four forces  but organizations also need to align the  culture and behavior with the technology.  It’s not enough to enable collaboration with technology but organizations need to do more.  One example coud be to incentivize individuals to collaborate and exchange knowledge. A simple and productive way to incentivize people is to use gamification techniques for process improvement.

What always excites me about attending Gartner conferences is seeing how our technology roadmap and in particular our upcoming  release lines up with  current and future technology  trends defined by Gartner.

Our ARIS 9 release is built on a cloud architecture, with  social collaboration capabilities at its core. ARIS  can be used on  mobile devices which  brings analysis of process information to your fingertips. The user experience has been enhanced  to make process improvement simpler and available to the  masses. I have been working with ARIS for over 10 years now and I must say (of course my opinion might be a bit bias) its never been  easier and more fun to improve processes and make them better.

But don’t take my word for it, make your own opinion. Attend our ‘ARIS 9 Innovations‘ webinar series where you’ll learn everything from what’s new in the latest release to how customers are driving new and improved value with their ARIS investment.  My next post will be a complete review of Jean Lastokas’s session on how Electrolux is changing the game through real-time supply chain visibility. Stay tuned!

The post Process Improvement trends at the Gartner BPM Summit appeared first on Reality Check.

Get this mix right, though, and loyalty pays huge dividends in increasing the lifetime value of a customer, lower acquisition cost through referrals and a positive brand association that creates new business opportunities.

Online retailers, like Zappos, Nordstrom and Expedia, are leading examples of a customer-focused culture that has helped them attract & retain customers and further grow their business via word-of-mouth marketing. The best way to enrich customer relationships is by making customers feel special in every interaction they have with your company. This can be accomplished by following these three maxims for customer delight:

1. Personalize the shopping experience
This includes not only personalizing the products offered to customers but also specially tailored content and promotions. Research shows that personalization can deliver five to eight times the ROI on marketing spend and lift sales 10% or more.

2. Acknowledge and reward customer loyalty
Send customers thank you notes with special offers to let them know that you appreciate their loyalty. This will drive repeat purchases, reduce customer churn, grow word-of-mouth marketing and increase customer lifetime value.

3. Invest in the right technology solutions
In-Memory Data Management (IMDM) solutions are the perfect fit to add velocity to your customer experience while enabling personalization, loyalty based rewards, fraud management and predictive customer analytics, all in real-time. Choose technology that can seamlessly integrate with your existing environment and make the job of enriching your customer relationships a lot easier.

What makes you a loyal customer to your favorite brands? Share your secrets on why you love some brands and not others.

(This blog was originally written on the Real-Time Big Data Blog and has been republished on Reality Check)

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