Information technology changes constantly like the climate, and successful organizations and software vendors like the human species have learnt to adapt in order to survive and prosper. Currently there are major head winds in IT - Cloud, Mobile, Data and cognitive science that are likely to cause disruptions in several industries. We have seen organizations adapt to earlier transformations like PC's and internet and the one's that got ahead of competition used IT to push their innovation agenda. Walmart is good example of a company that leveraged supply chain automation and intelligence to its advantage. We also saw the rise of companies like Amazon, Google and eBay that democratized commerce and information.
The last four decades could be viewed through the lens of major IT transformations and the type of enterprise software that companies adopted.
1.Mainframe era: 70's - Predominantly custom applications were developed for all aspects of business operations like accounting, inventory and production management, payroll and HRMS. IBM was the major provider of the platform for custom applications.
2.PC and network era: 80's - Access to information on user desktops with graphical user interfaces. Predominantly client server applications built on relational databases and GUI tools like Visual Basic and Power builder. Oracle and SAP emerged as major ERP vendors in addition to IBM and Microsoft who provided the platforms for enterprise application development.
3.Internet era: 90's - Web applications, e-commerce and the birth of the extended enterprise where companies were integrated with their customers, partners and service providers. Custom and packaged applications were built on middleware powered by application server farms and web pages using XML / HTML. Salesforce.com and more recently Workday emerged as SAAS vendors for CRM and HRMS.
4.Digital era: Current - Mobile apps that provide a rich user experience and the human interaction is defined by the smart phone touch paradigm. Enterprise applications are Omni-channel and have to provide a continuous experience across mobile / web and other channels. Cloud SAAS is the software delivery model. Uber is a great example of a company with a business model powered by digital technologies. Several new vendors are emerging and companies like Acquia, Twilio, Apigee and Act-on are experiencing exponential growth.
Bill Gates in 1990 at Comdex heralded his vision of information at your fingertips. The vision was right but I had pointed out at that time the challenges of access and integration with data that resided in custom enterprise applications in proprietary data architectures. The client - server and internet applications did not solve this fundamental problem and in fact compounded the issue with middleware and new data stores that were siloed. The approach that ERP vendors like SAP and Oracle found convenient was to surround the systems of record in the legacy systems in place. The current Cloud SAAS vendors are adopting the same approach as they see that organizations are unable to make a business case for a rip and replace of their current systems. The point I am leading to is that the challenges remain the same today and I list them below so that organizations could not only adapt to the current digital winds but make quantum leaps in using IT to get ahead of their competition.
Customer centricity and understanding customer needs
Knowing your customer has been a major desire for companies and CRM only partially solved this problem. Customer data is in multiple systems and in different formats. Master data management is critical to ensure accurate information regarding customers. In the digital era delivering appropriate and timely content based on real time data analytics is key to market segmentation and precision digital marketing campaigns.
Multiple administration systems and technology debt
The number of operational systems has not come down in most organizations as each era brought new applications in disparate technologies. The technical infrastructure underlying these applications are dated and becoming a major support burden. This has been consistently rated as the biggest reason inhibiting innovation. For legacy issues see https://www.insurancetech.com/what-matters-in-it-part-2-solving-legacy-with-acm/a/d-id/1314346?itc=edit_in_body_cross.
Mobile applications require integration across multiple systems to ensure rich customer experience
The customer experience design must cover all touch points starting with shopping, buying, payments and customer service. It needs to be designed to support multiple channels and a continuous experience needs to be provided across web and mobile apps. This is easier said than done given the issues stated above and the need for data quality. The amount of information per customer is growing non-linearly given the digital interaction points and the availability of cheap storage. The value of powerful machine learning tools and methods cannot be realized without organizing and analyzing structured and unstructured customer data.
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People skills and change management
Finally the biggest challenge is not technology but the people skills required in the digital age. A few critical skills that I see required are user experience designers, data scientists, digital information architects, machine learning and predictive modeling experts. Companies need to plan the pace at which they need to bring changes in business models, organization structures and operating models to derive the maximum benefit from digital transformation.
The organization of the future
The future is a hyper-connected world and all businesses will be dealing with peda bytes of data generated from devices that monitor all aspects of business activities. Retail stores with beacons, cars with telematics and individuals with wearable devices. IT leadership will no longer be the sole owner of bringing in new technologies. According to Gartner by 2017 fifty percent of the technology spend will be outside IT and will be by business managers. We are seeing new roles like Chief digital officer and Chief data scientist being defined and their responsibilities will span business, technology and operations. New age companies are disrupting traditional business models. Organizations therefore need to adapt rapidly in order to stay in business and innovation will be the major focus as opposed to operational efficiency which dominated the industrial era.
