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There is an interesting discussion initiated by Peter Schooff @bpm.com
Does Digital Transformation Begin with Process Transformation?
Digital Transformation Journey begins with the “Wake-Up Call” for Business:
• The current system has too many challenges to deal with
• The Legacy systems are getting next to impossible from a maintenance front
• Tough to get the specific skillset of developers in the market – for age-old technologies
• Our revenues are getting Hit YoY – time to rejuvenate our platform
• Our peers and competitors are making us run after money – need to do a complete fish-bone analysis of the system
• Are our systems future-ready & well equipped to adopt the nextGen technologies?
•……..and many more!!
Next, follows the :
- Envisaging the Business Model & Target Architecture (vision)
- Defining New Operating Model
- Process Optimization or Re-engineering Techniques (Process Transformation)
- Fitment Analysis (Wrap-&-Renew or Rip-&-Replace Model)
- Digital Technology Relevance/Mapping (strategy, compliance & regulatory)
- Implementation of the Changes
- Realizing the Re-Incarnated System (claiming Digitally Enlightened or Digitally Transformed)
At each and every stage mentioned above the C-P-Q factor (Cost-Pace-Quality) is validated to take appropriate decisions.
A detailed & insightful article on the transformation journey (by Dr Alexander S):
Happy Learning!! 🙂
Image source: link
BPM is no more a Healthy Salad Diet of plain & bland Process & Rules. It has matured and become an amalgamation of all the disruptive technologies and digital trends. In a nutshell, it has become more of a BRUNCH Meal.
The asks of the customers and market trends are cherry picked an packaged in a BPM Product – making it a self sufficient enterprise solution [at times] but on a lighter note Bulkier too [day-by-day the size of the BPM Product Installable is getting increased] 🙂
BPM Products (these days), keep adding some new feature into their kitty to make life easy for the Business as well as IT stakeholders. With new disruptive technologies getting mushroomed everyday, BPM packaged tools provide some flavor or slice of the new technology/trend. Its no longer an a-la-carte menu kind of offering for enterprise, instead a Packaged Combo Meal serving a set of business audience or business challenges/pain-points.
The features that were the key drivers and engine of BPM a decade earlier [during its inception] are getting enhanced [no doubt about it] but at the same time getting shadowed by the competitive chaos and disruptive tech. trends.
For every customer the four-walls within which they can experiment and play around with technologies / trends are the following : [these become the key focus areas for BPM Product Vendors]
- Un-parallel Customer Experience inline with the Enterprise Ux[User Experience]
- Enterprise Architecture – Guidelines/Standards/Compliance
- Cost-Pace-Quality [CPQ] Factor
- Business Strategy & Workforce Productivity
When we are at the verge of bidding farewell to the current year and welcoming the New Year. The curious question that keeps popping / itching at this time of the year
- “What are the BPM Predictions for the Next Year?” or
- “What’s cooking for BPM, in the next year?” or
- “What the Master-Chef BPM Product vendors have to Offer?”
- “Is the coming Year going to be BPMlicious”
…Stay Tuned for the Next Post on BPM Predictions for 2017!
Please do share your comments, thoughts and suggestions !!
Happy Reading 🙂
Last Year’s Post : What are your Predictions for BPM 2016?
Image Source: Link1 [The intent of using the images was to pictorially share the thoughts and share the learning. Happy to share Credits for the photos and images] Some of the pics have been taken directly from my Breakfast Table 🙂
— Peter Schooff (@PSchooff) September 20, 2016
Some really nice thoughts and comments/links.
MyPoV : How Do You See the Relationship and Interplay Between AI and BPM in the next Few Years?
The state we are in the BPM (Business Process Management) roadmap, was not realized overnight. It is getting enriched day-by-day by rattling with BPM in the enterprise playground with experience, learning, implementations, failures, scenarios and tagging along mushrooming disruptive technology trends. BPM with its inception as a process modeler/development /integration/orchestration/BAM etc. has matured as an enterprise wide platform to meet [more or less] the enterprise demands of transformation/mobility/decisioning/ACM/next best actions/mobility/social/analytics etc.
The same holds good for AI/Cognitive Computing. AI (“Artificial Intelligence”) is undoubtedly the “Nirvana” state which every enterprise/organization is trying to achieve as the final destination. But it does not happen over a blink of an eye, instead it is an evolving journey.
The journey to AI can be broadly classified as:
→ BASIC COMPUTING [scripts + repetitive steps in a single application]
→ ENHANCED COMPUTING [rpa + monotonous repititive job across applications]
→ COGNITIVE COMPUTING [machine learning + analytics]
- Basic Automation :
- Human with tools | structured data sets | Goal: Labor Efficiency
- Robotic Process Automation [RPA] :
- Human augmented with Robots | unstructured + patterned data sets | No Decisioning (targeted for Head Down Workers) | Goal: Labor Efficiency
- Autonomics :
- Robots augmented with humans | unstructured + patterned data sets | Goal: Labor Elimination
- Cognitive Computing :
- End to end robots with human oversight | unstructured + NO patterned data sets (targeted for Knowledge Workers) | Goal: Labor Elimination
- Artificial Intelligence – AI :
- Fully automated with NO human involvement | unstructured + NO patterned data sets (targeted for Knowledge Workers) | Goal: Labor Elimination
When we talk about the relationship and interplay between BPM & AI in next few years, the targeted enterprise audience is presumed to have matured over “enhanced computing” and addressed/identified all the underlying challenges w.r.t. monotonous manual intensive repetitive jobs/activities.
Some of the interesting use cases that enterprises can adopt based on the BPM + AI/Cognitive Computing duo are:
- Developing Self-Healing Processes [process optimization, exceptions and anomalies that are resurfaced during execution being auto corrected based on the past resolution steps → analytics & machine learning driven]
- Evidence based learning – data driven
- Adaptive and Predictive analytics + Past scenario based Actions [Machine Learning] for decisioning
- Virtual workforce controlled by Business Operation Teams
- Handwriting to Text or Speech (Identification & Learning Graphology Techniques)
- Debugging, Troubleshooting and Solution Wizard
- Text & Mail categorization/recommendation
- Support Issues and enriching KeDBs (Knowledge Error Databases)
- Self-Driving Cars – by building artificial intelligence and algorithms
- Image Processing
- Banking / Retail / Telecommunication
- Identifying Prospective Customers and Partners
- Satisfactory index of the Customer (based on relationship, transaction, marketing campaign etc.)
- Fraud, Waste and Abuse of Claims
- Forecasted Credit Risk and credibility of the customer
- Effectiveness of a Marketing Campaign
- Eg: How many accepted the offer and how many rejected it. Any decisive factors leading to acceptance.
- Cross Selling and Recommendations
- Eg: Ecommerce sites : People who purchased this product also purchased this
- Contact Center (helps the CSR to engage the customer during the call with the relevant data)
- Eg: We have seen that you have ordered the cheque books to a separate address (different from the registered address) – would you like to change your Address Details
- Healthcare & Life sciences
- Scanning & Screening – Biometrics
- Drug Discovery based on the component mix
- Diagnosis and remediation based on the Symptoms, Patient Record and Lab Reports
- AECP – Adverse Event Case Processing Scenarios based on drug, patient, geo, climatic conditions, past history, food intake etc.
- Handwriting / Signature / Fingerprint / Iris / Retina Verification
- Face Recognition
- DNA Pattern Matching
- ….and many more
Definitely, there are concerns in adopting the Artificial Intelligence on the Day-1 [it may not be a cake walk]. There are lot of factors that are getting disturbed from our traditional paths, and it is only a matter of time for the thoughts to sink , the dust around the buzz to settle down and most importantly GETTING the CONFIDENCE of RELYING BLIND-FOLDED on a MACHINE/ROBOT.
To cite a few scenarios: Are we comfortable and confident enough to sit in a driverless car or airplane? Or are we fine as a financial institution to manage all our high-profile privileged customers based on an algorithm? May be / May be NOT always.
- it becomes crucial from organizations to define the a bucket or business scenarios which can be an eligible candidate for BPM/Process & AI – avoiding RISKS that can have catastrophic effect on the customers/organization. To be precise, the RISK of Loss should not be more than the investment on AI.
- time and exhaustive scenarios are the key factors that will enrich the intelligence of the system based on real time transactions good[favorable] or bad[un-favorable] – is the business prepared for the same?
- it is important to have a balance between the enhanced customer experience and the operational cost reduction with virtual workforce
The business benefits that Enterprises can reap by augmenting BPM with Artificial Intelligence are:
- Reduced Operation Cost
- Elevated Customer Satisfaction / Experience
- Right Product to the Right Customer at the Right Time via the Right Preferred Channel
- Reduce Customer Churn
- Personalization through Prediction and Intelligence
- Increased Workforce Productivity
- Help organizations unlock the value of the wealth of data they have in-house
- Close the gap with the new online providers by offering real-time decisions
New terminologies like SPA [‘Smart Process Automation‘] are also coined, considering the process and cognitive computing/AI duo. Enabling the Process to select the best performing algorithm on the fly.
What is your take – How Do You See the Relationship and Interplay Between AI and BPM in the next Few Years?
Happy Learning 🙂
The Banking & the Financial services industry is the widely and wildly conquered sector where digitization and automation has been enabled to the max by IT. But in recent times, with the advancement of technology and innovations, it is important for the Banking industry to explore, pace up, transform, innovate, re-think and live in the present. The technology adoption and re-incarnation of business strategy/priorities to serve the customers will definitely play a crucial role in the Bank’s journey in making it stand tall n strong in the crowd (as a differentiator).
A nice read article on “Top Retail Banking Trends & Predictions“.
Key Highlights :
- The ‘Platformification’ of Banking
- Removing Friction from the Customer Journey
- Making Big Data Actionable
- Introduction of ‘Optichannel’ Delivery
- Expansion of Digital Payments
- Executing on Innovation
- Exploring Advanced Technologies
- Emergence of a New Breeds of Banks
- Mining New Talent
- Responding to Regulatory and Rate Changes
few additions …
- Next-Gen Customer Experience by including
- wearable device adoption
- analysis driven Next Best Actions
- ..and many more
- Developing Customer Centric Applications (primarily self service enabled)
- Welcome & Leverage Open Source Stacks (OSS)
- Crowd-Sourcing Initiatives (loan, mortgage, risk management etc)
- Blockchain technology making the financial system more decentralized
- Emergence of Banking Market Apps
- Robot Advisers that stop you from making unsound financial choices, in real time – Customer Assist
- Establishment of Banking Innovation Labs
- Beacon Technology Adoption
- Heat-Map Technology – Identifying right customer for the right product at the right time
- Automated Appointment/Scheduling/Token Management – helps avoiding unexpected crowd and long queues
- Battling with mushrooming Mobile Wallets
- DevOps driven CI/CD in IT – for streamlining Release Management
- Streamlining Operations in IT with Robotic Automation / Machine Learning techniques
Interesting Read Articles:
- 10 Branch Banking Innovation Strategies for 2016
- The Uberization of Banking
- What Makes a Great Mobile Banking App
- Digital Disruption Forces Financial Institutions to Rethink Priorities
- Selfies Transforming Mobile Banking
- With Digital Banking, Consumers Must Come First
- Internet of Things: Opportunity for Financial Services?
- Banks Need to Make Mobile Apps An Experience, Not An Add-On
- Article : The derivative effect: How financial services can make IoT technology pay off (link : pdf)
- 7 Habits Of A Highly Successful Digital Bank
- Differentiation in Banking Requires Better Data Insights
- New Customer Onboarding Goes Beyond Slick Marketing (link: pdf)
- Mobile Banking Satisfaction Drops As Digital Expectations Rise
- Banks Expand Innovation Investments to Battle Fintech
- How Banking Can Survive Digital Disruption
- Three Barriers to Banking Innovation
- Digital Thinking for Bank 1.0
- Becoming a Smarter Bank
What are your top trends & predictions in the retail banking space?
Happy Learning!! 🙂
A revolutionary step in the Datacenter Backup/Replication and Storage Technology – different from the traditional database replication approach wherein the the master data center is considered the Golden Source and Reservoir of Data and in case of any fail-over, the Master Data store overwrites the client side data (which in turn may affect the end user experience by wiping/overwriting any recent data) :
- Uber Goes Unconventional: Using Driver Phones As A Backup Datacenter (Article Source : Interesting Read – Detailed Article)
- How Uber Scales Their Real-Time Market Platform
- Reddit Link
Happy Learning!! 🙂
Enterprise Transformation is the fundamental change to the way an organization operates, whether that be moving into a new market or operating in a new way. It is an approach that attempts to align an organization’s activities relating to people, process and technology more closely with its business strategy and vision. This fundamental change aims to meet long-term objectives.
Enterprise Transformation is just like a journey and we never know when we will cross it again. At times we think, why every company is evaluating, developing and leveraging multiple products(be it for BPM, CRM, BigData, Cloud, Analytics and many other) in the market when its really going good.
Well there are certain drivers that poke the organizations to take these steps intentionally or un-intentionally.
So, whenever we get this question like “Why Enterprise Transformation for this Customer/Company ?” – it is very important to do our home-work with the set of drivers that could be one of the reasons. The following are some key drivers responsible for the organizations to go through the enterprise transformation phase.
- Legacy Modernization
- Product Support Decommission
- Competative Market Scenario
- Company Acquisition
- Current implementation – screwed up
- Legacy Modernization :
When we talk about legacy modernaization, it could be moving out of the age old black and white screens and bringing colours to life with a flashy responsive user interface. Additionally it is the lack of skilled resources in the market and maintainance/support cost for the legacy product.
Example : Transforming a project from AS400 or Fortran or C++ to a next generation HTML 5 based flashy ajax based UI
- Product Support Decommission :
Product Support decommission is just like sitting on a bomb with no-insurance. You never know when it will burst and some strange issue will pop-up and there will be no one around for rescue and provide support.
Example : Lets say(just think) Siebel 4.0 is used heavily in a customer site and Oracle announced that Siebel 4.0 will not be supported in furture and they are planning to decommission the product and its support as the latest versions of the products have been rolled out. So, in such a scenario the Company is in fix situation and has to decide whether it has to migrate the existing Siebel Stack to the latest version in the market or lookout for any competitors in the market with a better CRM offering suiting their business requirements.
- Competative Market Scenario
This is a killer instinct for a Company, trying to out-perform its peers with the features and functionalities it offers and racing with the current market leaders and trend setters.
Example : Lets say ICICI Bank, India provides a lot of fancy features like Mobile App, Social Integration, Self Service Portal, Next best Action – Cross Selling and IVRS/CTI support and many other multilingual features. But one other bank “XYZ”, though was a market leader the previous year if loosing its customer base as it is not able to service its customers via multiple channels or leveraging any other latest Technology. This can be a turning point and “huuh…its enough” situation and “time to transform and change”
It could also be a scenario where the customer wants to port the existing Java/JSP based project to an enterprise BPM/CRM based packaged product platform
- Company Acquisition
This something related to fate – you never know what’s gonna happen next!!
Every organization, whenever it does an acquisition, the one thing that will always be there in the back of the mind is – “How can I make a unified platform post acquisition and how easy/difficult/cost effective it would be ?”
Example : Lets say, a company ABC(1,00, 000 employees) acquired XYZ(20,000 employees) and consider a scenario if both the companies have different ERP systems (ABC uses Siebel while XYZ uses SAP) for maintaining the employee data and info. In such a scenario of trnsforming the existing business it is important to do some ground works. Lets say company ABC was waiting for past 2 years to come out of Siebel and go with SAP and this is that very moment and opportunity. Or it could be like, ABC company is very stable with its Siebel implementation and its is safe and less risky to port the 20,000 employee userbase in XYZ to Siebel and decommission SAP, than affecting the 1,00,000 userbase.
- Current implementation – screwed up
It is one such scenario where neither the Customer/Company nor the Vendor who was working on the project has any damn clue as to what exactly is going wrong. It could be a transformation from an architectural standpoint or introducing a service layer and working on some optimization from the data front.
Example : Lets say, a project was implemented by a vendor in the customer site and there were some performance and application challenges that resurfaced every now and then. For instance, whenever the number of concurrent users count reached 50, the server goes down, or memory leak issues. In this case, the application is perfectly fine but the way it is architectured needs to be transformed and modified, in the sense, an introduction of load balancer and increasing the scalability and flexibility parameters from a server view point or architecture needs to be refined as an enterprise transformational step. Sometimes, it can also be dealing with bigger and complex issues which can trigger the re-architecturing and re-designing of the entire system
Please feel free to write/comment/share your thoughts and suggestions when you worked as a part of an enterprise transformation program.
Happy Reading!! 🙂