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Business and Technology Insights

Optimize Your Business Costs with Emerging Technologies

 
November 9, 2017

When former McDonald’s USA CEO Ed Rensi stated in 2016 that it’s cheaper to buy a $35,000 robotic arm than it is to hire an employee who’s making $15 an hour bagging French fries, it caused quite a stir in the restaurant industry. Today, barely a year later, it is imminent that the cost benefits arising from deploying emergent technologies simply cannot be missed.

Cost optimization, lean and effective processes, agility, and productivity have always been necessary for any organization. Increasing pressures to improve the speed, volume, and quality in a cost efficient way is no longer an option for enterprises.

More than 1,800 digital platforms orchestrate our physical or human resources. Companies are recreating and adapting their business processes and offerings via emergent tech solutions such as robotics process automation (RPA), artificial intelligence (AI), machine learning and cloud computing, cognitive solutions, and straight-through processing (STEP).

Clearly, successful businesses today are those that do not shy away from new technologies but embrace and utilize them to open up new possibilities and save costs like never before. My whitepaper Transform Cost Optimization with RPA and Machine Learning  is packed with examples to illustrate how forward-looking businesses are achieving cost optimization to reach the next level with these technology solutions. It also talks about how companies are using these technologies in interesting combinations can increase savings and help conduct operations in a simple, timely, flexible, and scalable way.

With RPA and cognitive techniques, process automation today is no longer limited to repetitive tasks. It has progressed towards human-like behaviour including reasoning and responding to transform enterprise resource planning, human capital management, and digitize and simplify your customer experience.

Companies are successfully deploying machine learning to reduce errors and achieve scale when dealing with unpredictable situations. AdiMap a data science company is successfully using Amazon Web Services’ machine learning tool Elastic Beanstalk to provide its users and customers with financial intelligence at scale. The tool deployed and scaled web applications for AdiMap by processing data at scale for only a few thousand dollars a month.

An increasing number of organizations are moving their businesses from in-premise to cloud for increased accessibility, availability and scalability, at lower costs. Budgeting has become more predictable, over-purchasing is prevented through scalability, and IT staff is freed up to work on strategic operations.

Forward-looking organisations are adopting AI led products and services to remain competitive. Google is hiring top talent from the field and redefining itself as a machine learning-first companyBig players are partnering to formulate best practices and to open source many frameworks, algorithms, and tools such as TensorFlow and NuanceMix that help implement AI and machine learning solutions. The shift towards AI offerings is apparent, and it is driven by the fact that cost, scale, and performance efficiency is a clear benefit.

So don’t let your catch up curve fall behind the technology curve. If you want to achieve faster cycle time, enjoy higher computational speeds and efficiency for less money and energy, and respond to the changing market environment, tap into the emergent technologies. And the time to do it is now.

Vikas Gopal is the Global Managing Partner, Finance & Shared Services Transformation within Tata Consultancy Services. He has extensive experience advising senior executives on industry trends and strategies for shared services, finance, and digital transformation. Vikas has held leadership roles in consulting and has led the strategy, design, and implementation of several transformative programs.