4 Critical Reasons To Build Enterprise Apps

By Ben Kerschberg

Enterprise apps are changing the face of business. They increase worker productivity, leverage big data, and help optimize business process efficiency. Solely for the purpose of this post, I define the term “enterprise app” to include only those mobile solutions that face inward within the enterprise, including field workers, as opposed to externally facing such as a retail app.

There are at least four primary reasons for enterprises to build mobile apps. These are:

• Enterprise apps increase worker and overall corporate productivity.
• Enterprise apps empower field workers, who are changing the nature of corporate landscapes with their adoption of smart devices, especially tablets.
• Enterprise big data and analytics generate smarter apps than ever before.
• It has never been so easy to develop enterprise apps.

Enterprise Apps are Fueling Business Processes and Worker Productivity

Enterprise mobility is a “must have” for any competitive business, with future gains in worker productivity stemming in large part from enterprise mobility. Mobility results in (i) increased throughput (as measured by sales), (i) less inventory, and (iii) fewer operational expenses — three benchmarks identified by Eliyahu Goldratt in The Goal. Moreover, these efficiencies are realized by pairing mobile apps with data analytics. Mobile strategists must ensure that analytics relevant to business goals are wed to each mobile app in order to maximize that app’s utility. Analytics is a key part of the mobile software development life cycle, and continues to have benefits throughout the life of the relevant app.

Enterprise Apps Empower Field Workers

There is no shortage of companies that have workers in the field — delivery services, long haul truck drivers, and airport mechanics that keep planes flying safely, for example. Field workers are hardly new. What is new, however, is the fact that enterprises that implement the use of smart devices — and especially tablets — give workers real-time insights into the processes of which they are a part, and the ability to feed first-hand data from the ground back to the enterprise in a recursive cycle that results in data being analyzed instantaneously and then re-fed in the form of business intelligence to those workers’ devices.

Consider the following example:

Imagine a salesperson in the field who will be visiting three Fortune 500 companies in three different industries during the coming month. Meeting his quarterly sales figures depends on his success at these accounts. He is selling the enterprises the opportunity to build mobile applications that will help them expand their customer base, and thus spur corporate growth. The base app upon which client-specific solutions will be built is specific to verticals. In order to sell effectively at each account, he must have a deep knowledge of his prospects. He can get information in a variety of ways, including online sources such as Google Finance and published SEC quarterly reports. All of this is time consuming and unwieldy. Our salesperson needs help from his home base in the form of a mobile application that taps into a variety of available data — financial reports, press releases, third-party reports, market analyses, biographies of chief executives and influencers. Yet static information alone won’t do the trick. He will need his app to receive algorithmicly determined projections of various factors based on historical patterns.

He needs data in a timely manner before every respective meeting. Moreover, mobile moments exist in the life of a salesperson. A day before a meeting with an international oil conglomerate, historical patterns are not enough; our salesperson needs the app to inform him of federal regulatory changes passed the day before, mishaps at an oil rig the previous week, you name it. This data is vital, never again just “nice to have.” For the salesperson, it’s the difference between being prepared at huge accounts. For his company, it can represent the delta between meeting quarterly numbers or layoffs. And in this case, as for many for Sales processes, it boils down to this; to sell app dev to his prospects, our salesman needs a world class app of his ownEnterprise Big Data and Analytics Generate Smarter Apps Than Ever Before

Countless articles have been written about big data, and for good reason. Combined with AI and analytics, big data allows enterprises to infer business intelligence to keep them a step ahead. It’s hardly a stretch these combinations makes enterprises significantly smarter.