4 critical reasons to build enterprise apps
Smart companies are turning to enterprise apps to help manage the back-of-house productivity of their teams in the office and in the field. From salespeople leveraging data to power their meetings with prospects to truck drivers meeting delivery deadlines, big data is reshaping the corporate landscape. In this article from Forbes, learn about the rise of these apps.
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 least four primary reasons for enterprises to build mobile apps. These include:
- 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. The fact that these workers are in the field is 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 algorithmically 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 own.
Enterprise 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.
There are several critical elements as to how big data pertains to enterprise app development. First, it is bigger than ever, usually now expressed in exabytes – 10 to the power of 21 bytes and growing. Second, the overwhelming majority of data created over the past few years is unstructured in nature; i.e. data such as Microsoft Word documents, emails, videos, embedded sensor data, and telecommunications among thousands of other data types that do not fit in conventional databases. Third, almost none (0.5%) of this mountain of data has actually been analyzed – an extraordinary figure. This is changing with deep learning. This means that enterprises are sitting on gold mines. Analyzing big data isn’t easy, but neither is gaining market share at a lower cost. Yet as difficult as the process may be, it has never been easier, with a host of predictive analytics firms vying for enterprise attention.
Analytics-based and data-infused business intelligence informs enterprises of marketing opportunities or inefficiencies that can be addressed; for example, on the floor or a manufacturing plant or visibility into large-scale systems such as global supply chain management. Each of these marks a critical point: big data is not about data; big data is about business.
It has never been so easy to develop enterprise apps
Introductions to new marketplaces in the IT industry are game changers. Now that consumers have become used to purchasing apps, enterprises have overcome the inertia to build internal apps that they trust will be used. Usage in large part determines the value of an app. So how did mobile app development become so “easy” despite the fact that there are fewer talented mobile developers worldwide who can satisfy demand. In 2016, for example, there will only be five million app developers globally, an extraordinarily low figure given the enterprise opportunities on both iOS and Android platforms.
These opinions may rightfully give us pause, but they do not detract from our enthusiasm for mobile app development. Here’s why. The answer to the conundrum: “easy” development against in the face of a global lack of talent in new models for app development lies in new models for application development. One such model is crowdsourcing, which gives enterprises accessed to expert communities with software development skills. The community, often managed by a corporate entity, extracts from an app’s initial specifications those relevant parts that can be designed in simultaneously in parallel. Suitable solutions are then put together in a cohesive whole. The solution is less expensive and faster than a traditional mobile developer. Moreover, when the answer to a subset does not fit the solution, the self-selected programmers go back to the drawing board quickly. They fail fast, begin again, and deliver world-class solutions to forward-thinking enterprises.
This article was written by Ben Kerschberg from Forbes and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to firstname.lastname@example.org.