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April 28, 2021

Enabling an agile future requires a new approach

By: Guy Waterman | Senior Director, Product Strategy

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Today’s enterprises face challenges at an ever-increasing pace. In the pandemic-influenced age, leveraging past activity to forecast the future may no longer be a reliable guide to future performance. We are in an anomalous age, which requires different thinking and different approaches to achieve new standards of successful performance.

The pace of change has changed

Today’s enterprises face challenges at an ever-increasing pace. In fact, most of us have experienced more change in the last 12 months than we had experienced in the last 12 years. Yet how do most of us analyze what has happened; by viewing the same old monthly reports – maybe now every week? The analysis is essential when running a business and enables us to see what has happened – and potentially identify root causes to problems and catalysts for successful performance. While performing this kind of analysis is important, the vast amount of data considered combined with the pace at which it is changing causes organizations at risk; risk of overlooking a trend or missing out on an opportunity. With the pace of business change these days – data changes so quickly that when you figure out what to do about a situation–the opportunity to fix it has already passed and your team is on to their next challenge. To prevent missing opportunities, many organizations have taken to leveraging historical analysis to create forecasts of future outcomes.

The old way of doing things no longer works.

In the pandemic-influenced age, leveraging past activity to forecast the future may no longer be a reliable guide to future performance. COVID-19 and the frequency of such unpredictable changes experienced in this disrupted business climate make reliable historical trending virtually impossible. Historical trending is the basis of many statistical forecast-modeling functions. Now, these old forecasting models no longer apply. New patterns are emerging and those that can recognize and adapt to them quickly are the new leaders.

Evolving and automating analysis to learn from the past – to intelligently, immediately raise alerts about situations – enables teams to focus on what is important in the present. It enables them to take action before an opportunity to improve it passes them by. But, if the old models no longer work because the history creates errant forecasts or alert conditions are missed, what does that do to your team’s confidence about their solutions? What happens when your team no longer has advanced notice of problems in your business? How would you respond? 

Unprecedented times call for new approaches to business. Discover why you should analyze your business differently in the face of the COVID-19 pandemic (and beyond).

Data-driven enterprises need new approaches to enable an agile enterprise.

The erratic environment caused by the uncertainty of the pandemic has launched us into an anomalous age. It is a time at which you can say ‘what was once up, is now down', and you would be correct. To thrive in such times requires different thinking and different approaches. Organizations need new approaches to translate agility into productivity, and technology is at the core of that enablement. AI-enabled pattern recognition and anomaly detection enable you to make the transition from running your business (surviving) to guiding the business (thriving). 

AI-enabled processes learn from near-term experiences as opposed to relying on long-running patterns. AI can be tuned to recognize short-term trends and anomalies. The resulting actions can then alert the responsible teams to review – and then quickly take actions based upon prescribed actions. You needn’t place your entire organization in the hands of an AI-bot to be successful. Recommending actions can be just as effective as automating if you are not confident the trends identified do represent a risk/reward scenario for your organization. Choosing the right AI engine is as important as choosing the right statistical approaches. Tuning your team to work with these new business practices will provide the ability to take the right actions at the right times. Deploying AI in a business resiliency mode enables your team to perform more accurately and more effectively every time. Leverage recommendations to predict the future and prescribe actions that enable the achievement of improved performance. The point here is to create recommended or prescribed actions/steps to follow in order to follow through on the insights an AI-enabled business predictions solution provides.

Summary

The previous year taught us that agility is no longer an option, it is essential.

Relying on a ‘look back’ strategy keeps gets you stuck in the past, unable to experience consistent ‘break out’ events that propel you to the next level. Looking forward based upon the unique year we had and continue to have, may lead traditional forecasting solutions to provide incorrect insights spelling disaster for many pandemic weary teams. 

AI-enabled insights and augmented analytics provide the constant feedback and guidance necessary for the agile enterprise to quickly change, adopting malleable strategies that enable organizations to navigate the turbulent currents of today’s disrupted enterprise.

What are your thoughts? 

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Senior Director, Product Strategy
More about Guy Waterman
This is a syndicated post, view the original post here

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