Today, digital transformation is the new normal, leading to transformation of all functions and processes of an organization. This implies the need for a new “operating model” for almost every company globally.
Operations are, for all intents and purposes, fundamental to every business. Key objectives of operations teams are to simplify processes, reduce costs, and increase the value of business.
Disruptive technologies such as artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), Big Data, cloud, and blockchain continue to move into mainstream business, transforming processes and enterprise applications – leading to improved performance.
We are looking at making operations run “truly digital” to maximize your returns – your “bite” – in the cloud. The new house of operations will focus on cognitive and connected data.
Cognitive technologies present new opportunities to predict and respond more effectively to customer and market demands. They also open new approaches to connecting people and information – all of which will fundamentally change how buying and selling get done.
Given the vast amounts of data collected every day, one can only make sense of the patterns and provide integrations with the help of AI. Streamlining tasks through automation and augmentation will achieve greater efficiency with the help of ML and AI, building intelligence in the value chain, as AI and ML are set to disrupt all functions in the organization.
In the example of sourcing, a digital procurement assistant combined with machine learning can transform sourcing events by helping with tasks such as defining the correct request for proposal type; identifying appropriate suppliers to participate based on commodity category, region, or industry; and delivering intelligence on market signals and pricing pressures to optimize results.
Internally, operating a DevOps model in the company today is not just about agility but also about intelligence (predicting server loads, identifying problems much before a customer can spot them).
A culture of connectedness will focus more on customer needs by pushing decision-making to real time. Examples like 3D printing or drones delivering packages within minutes will require a change of the current operating model.
Today, in any IT operations department, many skilled colleagues are engaged in administrative tasks, monitoring, or troubleshooting manually, wading through many lakes of information that are not connected.
With RPA, we build a fully automated end-to-end process. The RPA takes information from various sources, making use of big data capabilities to gain better insights, and has a connected virtual team of bots who can help in running the operations better and at lower cost 24/7.
With ongoing digital transformation, the volume of information grows rapidly, the opportunity to gain insights accelerates, and data becomes the base layer of operations.
With data, we get smarter. In procurement operations, contracting can become smarter and more comprehensive with applications that can:
- Automatically identify relevant terms and conditions matched to legal library and taxonomy
- Uncover similar contract terms for a specific commodity by industry or region based on benchmarking data
- Suggest optimal prices to target based on expected volume and contractual discounts
With intelligent enterprises, organizations can invent new business models and revenue streams, monetize data-driven capabilities, and apply core business competencies in innovative ways. With increased adoption of solutions supporting the intelligent enterprise, back-end operations and support need to adopt to new operating models that are truly digital and intelligent. Operations teams can run internal operations efficiently, reduce operating costs, and allow the organization to become more profitable and adoption-relevant.
When do you plan to turn your enterprise into an intelligent operating model?
For more on digital transformation strategies, see Partnering To Deliver The Intelligent Enterprise.