For instance, your employees may be spending hours manually re-entering order information into the accounting and invoicing system, while other employees pull that same information from your CRM system for their order fulfillment processes and to calculate sales commissions.
If any orders are canceled in the meantime, your employees have to sift through mounds of data to reconcile this information again.
Such labor-intensive and manual tasks reduce the agility that your company needs to grow. Lack of Real-time Visibility: When software systems are un-integrated, you have multiple overlapping databases, and cannot easily get a view of business performance in a timely fashion.
Reports showing performance across your finance, sales, marketing, service, and fulfillment departments are crucial to giving you an integrated view of your company's operations.
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Most companies simply give up on acquiring this information on a regular basis because of the amount of time it takes to source, extract and analyze this data. For those that do, countless hours are wasted trying to tie unrelated, error-prone, and out of date information together. Consequently, businesses either end up making critical decisions slowly, based on inaccurate information, or they make hasty and risky decisions off of gut instinct.
Integration Complexity and Cost: With so many disparate applications, IT wastes an enormous amount of time and money on integrating, maintaining, and acquiring new versions of these applications. Often times, once new versions are purchased, even more integration and maintenance needs to be performed for all the different versions of software to work together. Consequently, valuable IT time that could be used to make the business more productive is wasted, while maintenance costs skyrocket.
Increased Customer Churn: Customer acquisition and revenue growth are key pillars to your company's continued success. With fierce competition, it is essential that your company provide an exceptional customer experience or risk having customers take their business elsewhere. When customers are unable to quickly get information on their order status, can't get issues resolved in a timely manner, or have to frequently deal with products being out of stock, they will be less satisfied and less likely to continue purchasing from you.
An integrated software system ensures that customers have the right information and customer experience and that your employees have the instantaneous access to all the customer information they need to service and sell to your customers. To keep your business growing at the dramatic rates you plan for, it is essential to have your business software applications integrated around a single codebase, database and business process.
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Vanguard, the investment services firm, uses cognitive technology to provide customers with investment advice at a lower cost. Its Personal Advisor Services system automates many traditional tasks of investment advising, while human advisers take on higher-value activities. By automating established workflows, companies can quickly implement projects and achieve ROI—but they forgo the opportunity to take full advantage of AI capabilities and substantively improve the process.
Most cognitive projects are also suited to iterative, agile approaches to development. To achieve their goals, companies need detailed plans for scaling up, which requires collaboration between technology experts and owners of the business process being automated.
Because cognitive technologies typically support individual tasks rather than entire processes, scale-up almost always requires integration with existing systems and processes. Indeed, in our survey, executives reported that such integration was the greatest challenge they faced in AI initiatives. Companies should begin the scaling-up process by considering whether the required integration is even possible or feasible.
If the application depends on special technology that is difficult to source, for example, that will limit scale-up. Make sure your business process owners discuss scaling considerations with the IT organization before or during the pilot phase: An end run around IT is unlikely to be successful, even for relatively simple technologies like RPA. The health insurer Anthem, for example, is taking on the development of cognitive technologies as part of a major modernization of its existing systems.
Rather than bolting new cognitive apps onto legacy technology, Anthem is using a holistic approach that maximizes the value being generated by the cognitive applications, reduces the overall cost of development and integration, and creates a halo effect on legacy systems. In scaling up, companies may face substantial change-management challenges.
At one U. The executive pointed out that the results were positive and warranted expanding the project. At the same time, he acknowledged that the merchandisers needed to be educated about a new way of working. If scale-up is to achieve the desired results, firms must also focus on improving productivity. Many, for example, plan to grow their way into productivity—adding customers and transactions without adding staff. Companies that cite head count reduction as the primary justification for the AI investment should ideally plan to realize that goal over time through attrition or from the elimination of outsourcing.
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Our survey and interviews suggest that managers experienced with cognitive technology are bullish on its prospects. Although the early successes are relatively modest, we anticipate that these technologies will eventually transform work. We believe that companies that are adopting AI in moderation now—and have aggressive implementation plans for the future—will find themselves as well positioned to reap benefits as those that embraced analytics early on.
Through the application of AI, information-intensive domains such as marketing, health care, financial services, education, and professional services could become simultaneously more valuable and less expensive to society. Business drudgery in every industry and function—overseeing routine transactions, repeatedly answering the same questions, and extracting data from endless documents—could become the province of machines, freeing up human workers to be more productive and creative.
Cognitive technologies are also a catalyst for making other data-intensive technologies succeed, including autonomous vehicles, the Internet of Things, and mobile and multichannel consumer technologies.
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The great fear about cognitive technologies is that they will put masses of people out of work. Of course, some job loss is likely as smart machines take over certain tasks traditionally done by humans.
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However, we believe that most workers have little to fear at this point. Cognitive systems perform tasks, not entire jobs. Most managers with whom we discuss the issue of job loss are committed to an augmentation strategy—that is, integrating human and machine work, rather than replacing humans entirely.
We believe that every large company should be exploring cognitive technologies. There will be some bumps in the road, and there is no room for complacency on issues of workforce displacement and the ethics of smart machines. But with the right planning and development, cognitive technology could usher in a golden age of productivity, work satisfaction, and prosperity. Thomas H. Rajeev Ronanki is a principal at Deloitte Consulting, where he leads the cognitive computing and health care innovation practices. Some of the companies mentioned in this article are Deloitte clients.
James Wheaton and Andrew Nguyen. Davenport Rajeev Ronanki. Executive Summary Cognitive technologies are increasingly being used to solve business problems; indeed, many executives believe that AI will substantially transform their companies within three years.