Monday, May 07, 2018

Product Management - Managing SaaS Offerings



If you are a product manager of a SaaS product, then there additional things one needs to do to ensure a successful customer experience - Manage the cloud deployment.

Guidelines to choosing the best data center or cloud-based platform for a SaaS offering

1. Run the latest software. 

In the data center or in the IaaS cloud, have the latest versions of all supporting software: OS, hyper visors, Security, core libraries etc., Having the latest software stack will help build the most secure ecosystem for your SaaS offerings.

2. Run on the latest hardware. 

Assuming you're running on your data center, run the SaaS application on the latest servers - like HPE Proliant Gen-10 servers to take advantage of the latest Intel Xeon processors. As of mid-2018, use servers running the Xeon E5 v3 or later, or E7 v4 or later. If you use anything older than that, you're not getting the most out of the applications or taking advantage of the hardware chipset.

3. Optimize your infrastructure for best performance.

Choose the VM sizing (vCPU & Memory) for the best software performance. More memory almost always helps. Yes, memory is the lowest hanging of all the low-hanging fruit. You could start out with less memory and add more later with a mouse click. However, the maximum memory available to a virtual server is limited to whatever is in the physical server.

4. Build Application performance monitoring into your SaaS platform

In a cloud, application performance monitoring is vital in determining customer experience. Application performance monitoring had to be from a customer perspective - i.e., how customers experience the software.

This implies constant Server, Network, Storage performance monitoring, VM monitoring, application performance monitoring via synthetic transactions.

Application performance also determines the location of cloud services. If  customers are in East coast - then servers/datacenters should be in east coast. Identify where customers are using the software and locate the data centers closer to customer, to maximize user experience.

5. Build for DR and Redundancy

SaaS operation must be available 24x7x365. So every component of SaaS platform must be designed for high availability (multiple redundancy) and active DR. If the SaaS application is hosted on big name-brand hosting services (AWS, Azure, Google Cloud etc) then opt for multi-site resilience with auto fail over.

6. Cloud security

Regardless of your application, you'll need to decide if you'll use your cloud vendor's native security tools or leverage your own for deterrent, preventative, detective and corrective controls. Many, though not all, concerns about security in the cloud are overblown. At the infrastructure level, the cloud is often more secure than private data centers. And because managing security services is complex and error-prone, relying on pre-configured, tested security services available from your cloud vendor may make sense. That said, some applications and their associated data have security requirements that cannot be met exclusively in the cloud. Plus, for applications that need to remain portable between environments, it makes sense to build a portable security stack that provides consistent protection across environments.

Hybrid SaaS Offering

Not all parts of your SaaS application can reside in one cloud. There may be cases where your SaaS app runs on one cloud - but pulls data from other cloud. This calls for interconnect between multiple cloud services from various cloud providers.

In such hybrid environment, one need to know how apps communicate and how to optimize such a data communications. Latency will be a critical concern and in such cases, one needs to build in a cloud interconnect services into the solution.

Cloud Interconnect: Speed and security for critical apps

If the SaaS App needs to access multiple cloud locations, you might consider using a cloud interconnect service. This typically offers lower latency and when security is a top priority, cloud interconnect services offer an additional security advantage.

Closing Thoughts

SaaS offerings has several unique requirements and needs continuos improvements. Product managers need to make important decisions about how the applications  are hosted in the cloud environment and how customers experience it. Making the right decisions gives the results for a successful SaaS offering.

Finally, measure continuously. Measure real-time performance, after deployment, examining all relevant factors, such as end-to-end performance, user response time, and individual components. Be ready to make changes if performance drops unexpectedly or if things change. Operating system patches, updates to core applications, workload from other tenants, and even malware infections can suddenly slow down server applications.

Friday, May 04, 2018

Key Technologies for Next Gen Banking



Digital Transformation is changing they way customers interact with banks. New digital technologies are fundamentally changing banks from being a branch-centric human interface driven to a digital centric, technology interface driven operations. 

In next 10 years, I predict more than 90% of existing branches will close and people will migrate to digital banks. In this article, I have listed out 6 main technologies needed for next gen banking - aka the Digital Bank.

1. MobileMobile Apps is changing how customers are interacting with bank. What started as digital payment wallets, mobile banking has grown to offer most of the banking services: Investments, Account management, Lines of credit, International remittances etc., providing banking services anywhere, anytime!

2.Cloud & API

Mobile banking is built on cloud services such as Open API & Microservices. Open API allows banks to interact with customers and other banks faster. For example, Open API allows business ERP systems to directly access bank accounts and transfer funds as needed. Open API allows banks to interact faster, transfer funds from one back to another etc. In short Cloud technologies such as Open API and microservices are accelerating interactions between banks, and banks & customers, thus increasing the velocity of business.

3. Big Data & Analytics

Big data and analytics are changing the way banks reach out to customers, offer new services and create new opportunities. Today banks have tremendous access to data: Streaming data from websites, cloud services, mobile data and real time transaction data. All this data can be analyzed to identify new business opportunities - micro credit, Algorithmic trading etc.

4. AI & ML

Advanced analytical technologies such as AI & ML is increasingly being used to detect fraud, identify hidden customer needs and create new business opportunities for banks. Though these technologies are still in their early stages, it will get a faster adaption and become main stream in next 4-5 years.

Already, several banks are using AI tools for customer support activities such as chat, phone banking etc.

5. Biometrics & security.

As velocity of transactions increases, Security is becoming vital for financial services. Biometric based authentication, Stronger encryption, continuous real time security monitoring enhances security in a big way.

6. Block chain & IoT

IoT has become mainstream. Banks were early adapters of IoT technologies: POS devices, CCTV, ATM machines, etc.  Block chain technology is used to validate IoT data from retail banking customers. This is helping banks better understand customers and tailor new offerings to create new business opportunities.

Bitcoin Hype has ended: What's Next? Answer is Corda!


Bitcoin and Blockchain A number of things have come to pass since 2016.  post (below the line) including Bitcoin forking in order to increase transaction speed. This happened suddenly, after what appears to be a reversal of policy by China whose companies control 80% and all 5 of the largest bitcoin "mining pools."

Chinese companies blocked bitcoin forking for an extended period except Alibaba's ANTpool. Suddenly all five approved the XT and then Classic fork and voila. What happened? We can only speculate, however it appears the Chinese government decided it was better to control Bitcoin than attempt to block it. So yes, Bitcoin is a "distributed" governance model but make no mistake that Bitcoin governance stops in Beijing.

What is Corda?

Corda is a blockchain platform built for business. Corda removes costly friction in business transactions by enabling businesses to transact directly. Using smart contract and blockchain technology, Corda allows existing business networks to reduce transaction and record-keeping costs and to streamline business operations. Corda enables an interoperable, open network that empowers organisations to collaborate and transfer value directly with trust. Corda achieves this with complete privacy in a freely available open source software platform.

Corda can be deployed on Generic x86 Servers






Thursday, May 03, 2018

Data Analytics for Competitive Advantage



Data Analytics is touted as 'THE" tool for competitive advantage.

In this article, I have done a break down of data analytics into its three main components and further listed down various activities that are done in each category.

Three Main Components of Data Analytics

1. Data Management
2. Standard Analytics
3. Advanced Analytics

Data Management


Data Management forms the foundation of data analytics.  About 80% of efforts & costs are incurred in data management functions. The world of data management is vast and complex, it consists of several activities that needs to be done:

1. Data Architecture
2. Data Governance
3. Data Development
4. Data Security
4. Master Data Management
5. Metadata Management
6. Data Quality Management
7. Document & Content Management
8. Database & Data warehousing Operations

Standard Analytics

Standard Analytics is what most businesses have been doing for a long time now. Standard business reporting, Alerts etc., There are several standard analytics functions that business needs for day-to-day activities.

1. Standard Reporting
2. Ad hoc queries
3. Data filtering
4. Alerts
5. Clustering
6. Trend Forecasting
7. Statistical Analysis

Advanced Analytics

Advanced Analytics is what getting all the attention. Big data & analytics using modern algorithms such as Map Reduce. In addition to big data, Advanced analytics includes newer technologies such as AI, ML, RPA etc.

1. Predictive Analytics
2. Prescriptive Techniques
3. Operations Optimization 
4. Simulation Modelling 
5. Machine Learning
6. Artificial Intelligence
7. Robotic Process Automation
8. Deep Learning


Closing Thoughts 

It often assumed that advanced analytics gives competitive advantage. While this statement is TRUE, the foundation of business analytics is in data management and basic analytics - without which advanced analytics will not provide the desired competitive advantages.

One must also note that the level of complexity, costs, and efforts increase exponentially as one moves to advanced analytics. New investments are needed in terms of newer IT infrastructure, software tools, people skills and talent. So companies must be ready to invest to get competitive advantage.

Wednesday, May 02, 2018

Rise of Robo-Advisors!

Robo-advisor  brings down the cost of such services to those investors who otherwise couldn't afford.

Lower cost plus rapid execution of trades based on algorithm gives better results. No wonder people are moving to robot advisors.