Industry Context

CIOs of B2B companies are faced with many challenges. They are to build more applications, at a faster pace with fewer resources. They have to integrate broader and deeper sets of data. All while being compliant and ensuring security. Employees must be enabled on the road; suppliers have to be brought closer to the organization. Communication channels have vastly expanded. Architecture models have proliferated, modernized and evolved.

Value Proposition

The solution: agile applications, delivered in a hybrid way, with end-to-end methodology delivered via measurable ROI. Software AG Live is a platform with 3 interlinked capabilities that deliver business agility and time-to-value, precisely addressing the challenges in the B2B space. The platform allows for the rapid development of applications that adjust to evolving business needs, their integration with legacy ground or cloud based systems and the business process documentation thereof.

Target audience

Focus for Software AG remains the Global 2000 and governmental audience. However, due to the lower barrier of entry that cloud represents, aspiring mid-sized companies will now also be able take advantage of Software AGs’ history of innovation. Beyond its traditional IT base, Software AG Live is particularly attractive for the business analyst profession and subject matter experts. Not only will they be able to design processes unique to their business area with Process Live (available Q3 2013), but they will also be able to implement them with AgileApps Live (available now). Finally corporate IT will be able to integrate these with existing systems using Integration Live (available Q1 2014).

As-a-Service

In developing our cloud proposition, Software AG paid particular attention to getting the service experience right. Amongst others, AgileApps Live, based on the recent LongJump acquisition, comes with self-service purchasing, automatic on-boarding and zero delay to deployment. This service orientation will be extended to the rest of the suite, a unique experience in the PaaS sector.

Differentiation

Three things allow Software AG Live to stand out. Firstly, on-premise, private cloud and public cloud are treated as equals. In other words 40+ years of on-premise innovation are now also available in the hybrid cloud. Second, data privacy and security are at the forefront of the service delivery experience. Diligence is given to ensure data is treated according to the world’s most comprehensive data protection laws and standards, which are further supported by leading security processes and technology. Finally, Software AG live is a unified platform with integration between its various sub-components.

Market promise

Software AG Live will …

1. Allow Capex to Opex transformation
2. Have returns measured in agility and time-to-market
3. Protect investments through high information security and data privacy

The post Introducing Software AG Live! A different approach to cloud computing that will stir up the PaaS market appeared first on Reality Check.

Today, there are four approaches when it comes to cloud integration. Let us look at them one-by-one and understand the pros and cons of each approach.

1. Point-to-point integration – This is the quickest and dirtiest approach in the book. This is when your developers have an all-night hackathon to create scripts and code snippets to connect one application with another (cloud or not). This model may work with a small company where only two or three applications need to be tied together. As is obvious, this approach is not scalable at all by any means. Code maintenance, upgrades and future development soon become nightmares. You can forget about IT agility to business needs as the company starts to expand.
2. On-premise integration solution – This approach can be easily adopted by companies that already have an integration infrastructure / Enterprise Service Bus (ESB) in place. They can just leverage the existing integration platform to connect with on-premise applications as well as SaaS applications. This is provided that the integration solution that you are using has such capabilities and framework to connect with any SaaS application seamlessly. Otherwise, you will end up having more developers coding their way out of this. The other point to also consider is that this is not a cloud solution.
3. iPaaS (Integration Platform as a Service) – In the last couple of years, this model has been gaining some maturity and attention amongst small companies. Enterprises that do not want to spend much on their infrastructure but still be more agile, adopt SaaS applications as needed. As an extension to the same methodology, the same enterprise also adopts an integration solution hosted by the solution provider themselves. This is called an iPaaS. This allows companies to not worry about setting up, maintaining and managing a complex integration infrastructure to integrate with SaaS applications. On the same note, I should also emphasize that an iPaaS is not a replacement for an ESB. As a matter of fact, Gartner predicts that more and more companies are going to adopt a hybrid integration infrastructure comprising of both an on-premise ESB and an on-cloud iPaaS.
4. Cloud Services Brokerage – This is very similar to the iPaaS except that in this case, even the development and maintenance of the integration maps and services are done by the solution provider themselves. Only very few small vendors offer this type of solution. This model has not caught on to the mainstream market yet. Not a lot of companies are willing to trust outsourcing their entire integration development to a third-party. So, for the sake of this conversation here, I am not going to spend any time on this topic.

There is no such thing as the “ideal way” of how you should integrate with the cloud but there are definitely right and wrong ways of doing so. Given the four approaches above, you are better off with either option 2 or 3 based on the size of your IT department, your application infrastructure, your existing integration architecture and future growth plans. iPaaS will definitely give you greater flexibility in scaling up your integration infrastructure based on how your business grows. But, in the interim, as you step up to adopt an iPaaS, a hybrid architecture of option 2 and 3 together might be more beneficial for various reasons. We will discuss this in a later post in more detail.

Software AG launches Integration LIVE (iPaaS)

With the acquisition of LongJump, Software AG has positioned itself in a very strategic position to guide its 4000+ customers in addressing the cloud integration challenges. As a part of its most exciting launch of version 9.0 set of products in June 2013, it will be releasing webMethods CloudStreams, which addresses bullet #2 in the above list of approaches. For more information on that product, you can click on this link.

Today, Software AG announced an even more exciting future plan for our cloud strategy – Software AG Live, the first cloud-based Platform-as-a-Service (PaaS) suite. Amongst the three components that make up Software AG Live, the one that is of interest in this particular scope of conversation is Integration Live. This is an integration PaaS which enables cloud-to-cloud integration and seamlessly connects with private cloud or on-premise Enterprise Service Bus (ESB) installations. Integration Live will offer an unmatched combination of ease-of-use and enterprise-strength and will be compatible with webMethods Integration Server, the market leading ESB from Software AG. Availability is scheduled for Q1 of 2014.

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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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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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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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Introducing Big Data’s cousin Big Services. What you never heard of Big Services? Well Big Services is perhaps a little shy. OK being a little tongue-in-cheek here but services are proliferating very very fast. And the business opportunity is just as big as taming Big Data.

Services are not a new concept; they started as design guidelines to creating reusable services, evolved to Service-Oriented-Architecture (SOA), and the now to API management. What is amazing is that we are in the age of service proliferation – by one measure public services that can be accessed over the internet are doubling every year and that excludes the hundreds of thousands of services inside the enterprise. Add to this the whole new suites of Software-as-a-Service (SaaS) offerings it becomes a nightmare to even know how many services are out there.

The sheer volume of services is one reason we could call them “Big Services”, but it is the complexity of the different service interfaces, issues of access and control, monitoring, lifecycle management, governance and access that make them really Big Headache Services!

Consider SalesForce.com which has one API (well that seems easy enough) but has a 1,000 page document describing how to access it (OK not so easy). Workday’s opposite approach of publishing 100’s of API’s with 6 or 7 versions. Each WSDL and schema is unique, with different data types (which many need translation form one API to the next), different dependencies (ordering of API calls make a big difference to the end results) and different security and access requirements.

In order to keep track of these Big Services (Volume and complexity) is no easy task. There is a need for software to help you do this. The software needs to provide repository services and a level of abstraction that ensures you work at solving the business problem at hand and not the complexity of the services call. Naturally the software needs to take care of error handling (like what to do if the service is unavailable), monitoring (like checking if the API is available and the average time per call), lifecycle management (like which version of the service to call) and a host of other service security and dependency checking needs. It comes down to whether you have time to build this software of buy it from a trusted partner.

Big Services are creating Big Opportunities: Online services such as Google, Facebook, Netflix and eBay are handling billions of application programming interface (API) calls per day and some companies are accounting for billions of dollars in revenue per year via API links to their services, according to John Musser, founder of ProgrammableWeb. Enterprises are finding that exposing their systems to the world as services create amazing opportunities, just like Best Buy who allows shopping and fulfillment via their API’s, or the EPA which serves up hundreds of self-service APIs that handle air quality to UV index monitoring, or 7-Eleven who exposed coffee purchase API information to determine the results of the election. It isn’t a matter of if, but a matter of when you expose your services to the self-service world, but if you don’t you will miss this BIG services opportunity. Naturally exposing internal systems as services creates its own set of Big Services Headache – stopping denial-of-service attacks, securing the service, publishing the WSDL and documenting the interfaces, and providing access to these services across the mobile and web world.

How will you take advantage of this Big Services opportunity, and provide your business with Big returns?

The post Big Data Meet Big Services appeared first on Reality Check.

If you have a mobile strategy, you’re going to be using API’s.

It’s the “only way*” to support the breadth of devices to natively access corporate digital assets.

If you are already delivering API’s, and delivering them across different teams/businesses to enable a mobile strategy, why not just expose those same API’s to everyone and see what happens?

I’ll tell you what happens… people will solve problems.

IT will need to pivot.

IT’s job will become that of an enabler. Enable people to solve problems while protecting their company’s digital assets and ensuring business-critical applications remain going-concerns.

Think on this, it’s exciting.

*  It’s never the only way

The post Mobile & API’s are Two Sides of the Same Coin appeared first on Reality Check.

In fact, I think one of the things that I do best is explain complex ideas in ways others can understand, and so that they realize how the idea is relevant to them.

While technically not a metaphor, I really like the idea of comparing API’s to Excel formulas in the context of the “everyone learning to code” trend. It came up in yesterday’s API Management Demystified webinar.

Many businesses run complex models in Excel. In fact, Excel was, in many ways responsible for the JP Morgan Chase “London Whale” that cost them billions. (In my opinion, Excel wasn’t responsible, rather it was a lack of governance that allowed people using Excel to fail in a very big way, but that’s a-whole-other conversation.) James Kwak has a smart article about the importance of Excel to business, and why running a business on Excel is such a mess. James’ key difficulties with Excel:

• There’s no governance or auditing.
• There’s no ability to test if the spreadsheet is working (and importantly, if it’s still working).
• There’s a very low barrier to entry (anyone can create one).

Another thing I’m really good at is being lazy. I abhor inefficiency, and simply refuse to do things twice when they can be automated with just a little extra effort. It’s not just about efficiency, by the way. It’s about art.

When I started my career, I was writing a boatload of proposals for network integration solutions. I totally tricked out Excel. Doing so saved me hours off each proposal, possibly hours a day.

My proposals were art*. Why? I was able to focus on proposal content and the deseign because I had automated so much of the crap-work. Plus, my proposals were simply better because they’d be more correct (I embedded error checking in the spreadsheet each time I made a mistake, so I’d make the mistake only once).

I can’t be the only lazy person out there.

Things have changed since the early 90′s. Today, people are using their mobile devices for everything. In fact, just this morning I took a picture of my wife, my baby, and my iPhone as we were having a family moment! (OK, I’m odd.)

Not everyone is going to want to start their own company. Some lazy people have corporate jobs. And, they will want to write their own applications instead of the spreadsheets that the earlier generation-of-lazy would write.

And, that’s where API’s come in.

API’s will make corporate resources (processes, events, & data) available to lazy people all over corporate America to make things more efficient.

The only thing is, just because “everyone knows how to code” doesn’t mean “everyone understands programming”.

The same challenges that James points out in his article apply with an even greater degree to software.

Why to a greater degree? Because software that uses API’s will be everywhere, not just “locked in Excel”.

That’s where API Management comes in to play.

Companies that want to capture the innovation going on in the mobile & API markets, or that want to take advantage of their most motivated employees (the lazy ones), are going to have to create an environment where problems can be solved with software using digital corporate assets. The only way to do this successfully is to deploy an infrastructure supporting these efforts that delivers governance, lifecycle management, and self-service testing & support.

* I still have some in storage along with the personal letters of thanks from customers.

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To capture the Big Data opportunity, manufacturers are quickly moving data out of slow disk-bound databases and into ultra-fast machine memory. Here are 10 ways that manufacturers can benefit from in-memory data management:

1.  Product design & development
Easily experiment with different design options for products by instantly manipulating large design files held in-memory.
2.  Planning & forecasting
Use terabytes of multiple data sets and historical information, in memory, to develop more accurate plans and forecasts.
3.  Contracting
Flag contract and service-level agreement (SLA) violations in real time.
4.  Procurement
Highlight best and worst performing vendors by comparing performance against a set of KPIs.
5.  Supply Chain
Optimize sourcing of raw materials from multiple vendors and track inventory positions in real time, even across multiple geographies and company divisions.
6.  Operations
Intelligently parse data from sensors and telematics to avoid breakdowns, conduct preventive maintenance, and improve manufacturing output.
7.  Marketing
Understand and refine marketing campaigns based on social feeds, customer reviews, and buying patterns.
8.  Logistics
Optimize truck routing in real time to boost delivery speed while reducing fuel costs.
9.  Customer Service
Delight customers with fast service by keeping profiles and account histories in memory.
10.  Maintenance
Gather real-time sensor data from shipped products to quickly gain intelligence about what causes breakdowns.

Simply put, in-memory computing is a big competitive differentiator for manufacturing companies. Have you moved your manufacturing business in-memory?

The post 10 Reasons Why Manufacturing Is Moving In-Memory appeared first on Reality Check.