Among the sea of social media apps, news apps, and photo book-making apps I use – I have three kids! – is my mobile banking app. I bank at a “traditional” or “retail” bank, meaning it has branches, versus an online-only bank. That being said, I never go to a branch. Anything I need to do I can do using my mobile banking app: check my transactions, transfer money between accounts, or deposit a check. Believe it or not, these things that users have come to expect out of their mobile banking experience, I have had to figure out rather the hard way with my current mobile banking app. The user experience of my bank’s app has never been truly intuitive, though it has gone through multiple iterations. Banking apps should not make it difficult for customers to complete basic tasks. By continuously putting user experience first and applying the following adjustments to your UX Strategy, your bank is guaranteed to drive revenue through customer loyalty.
The first time I used Venmo, an app designed solely for people to be able to electronically send money, I immediately noticed the intuitiveness of the app. A few months after I started using Venmo, my bank came out with an identical feature. I could send money to friends or family no matter who they banked with. That’s as much as I know about it because the idea of using my bank’s clunky app for a task I found myself doing frequently seemed overwhelming, so I stuck with Venmo.
As more FinTech companies continue to disrupt, develop and innovate mobile banking applications, it will occur at the expense of lost market share for traditional banking institutions.The rising FinTech sector is making it easier making it easier for their customers to do more with their money.
At Shockoe we have advised our financial industry partners to consider two adjustments to their UX strategy as a result of this changing environment:
Implementing machine learning.
I, like many others, have predictable spending habits. I shop at the same places, I pay my mortgage, and I head to the grocery store at the same time. To keep an eye on my spending, I log into my banking app quite regularly.
The reason I point out these things is that this is all data that the banks can use to help make me a “stickier” client. I get random ads sometimes when I log into my account, but they don’t happen as I take an action, nor are they personalized to me.
Banks are leaving a great opportunity to interact with their customers on the table. They could ask questions about unusual spending to improve security and more importantly learn about shifting habits. e.g. “It looks like you made a purchase at Wegman’s last weekend, was that you?”, the app learns that this is now part of my purchase history and the algorithm changes. Similarly, new products could be touted as client data captures what looks like a night out: “Looks like you left the kids at home and recently went to the movies! Did you pay your babysitter with our easy system to send money electronically to people?”
There should always be a way to turn these kinds of alerts off, but banks know so much about their users, and using machine learning capabilities is one way they can use that data to try to engage more with their clients.
Making banking apps more social.
A big part of Venmo’s popularity comes down to the fact that they’ve tapped into the special sauce of why social media is so popular/addictive. You can interact with people, keep up with their latest transactions and see why they’re sending or receiving money for. Obviously, security is n essential consideration in banking, but for people that are willing to share, this is another outlet for banks to engage their audience, encourage product use, and compete in an increasingly competitive FinTech industry.
Do people want to be able to brag about their savings account interest rate? What else are people comfortable with being able to show off in regards to their banking relationship? We work with our clients to run user group feedback sessions to find the answers to things like this. User feedback should be an essential consideration in designing an engaging user experience that extends beyond logging in and checking on account statements.
Banking apps should no longer think of themselves as a one dimension account statement viewing portal. FinTech will eventually edge them out of services such as peer to peer payments (venmo), machine learning (mint), and potentially edge them out of being a provider at all in lucrative services. I am a project manager at Shockoe and I’ve worked with two large banking clients as part of my tenure here, and these thoughts are coming from meetings with them and our approach helping them stay engaged with their user base and attract more users through their mobile app solutions. What’s cool is our clients know we work together to create mobile applications that people use, love, and remember, and that sometimes the problems are even solved by the project management team.
Thousands of companies have adopted enterprise mobile apps during a time when they were becoming popular and they wanted to “check the box” that they had an app. While most companies understand the benefits of mobile technology, unfortunately, some have failed to exercise due diligence when developing their app and selecting the proper vendor for their project. There are many great mobile development firms out there, but making sure you have a good fit for a particular project is the most important factor to consider when selecting a vendor. Let’s go through the checklist of items that should be considered any time your organization wants to develop an enterprise app.
1. Does the developer have previous experience with similar projects?
This is an important question to ask because the quality and agility of the project will be significantly better if the mobile dev team has completed a similar project before. For example, if you’re in the banking industry, look for a firm that has made banking apps before. They may have made other great apps for other industries, but that doesn’t always translate into a successful project in yours.
2. Does the vendor have a dedicated UI/UX team?
If the answer is no, immediately disqualify that vendor. Huge mistake companies have made was neglecting the end-user experience. The “it doesn’t matter if it looks that great because they have to use it anyway” line of thinking is counterintuitive with the premise of increasing employee work performance and satisfaction. A dedicated and experienced UI/UX team will make sure the app is intuitive. After all, a user interface is like a joke—if you have to explain it, then it’s not very good
3. Look at customer reviews.
Most mobile agencies, if they have been in the industry long enough, will have customer reviews. These can be found on sites like Clutch and GoodFirms and can provide great insight into how successful similar projects were and how easy it is to work with their team.
4. Get to know the team.
When selecting the right firm, get to know the team that will be assigned to your project. Typically a team will consist of a couple developers, a designer, and a project manager. It’s important to get to know these people to determine how easy it will be to work with them, and also to decipher if they are qualified to take on your project.
5. Look for someone who is concerned with the overall objective, not just the app.
Mobile agencies need to understand the “big picture” that the client wants to accomplish. Some developers may get caught up with the app development and making it really “sweet,” which is good, but clients don’t care about how cool the app is if it doesn’t address the business objectives it is supposed to help accomplish.
6. Don’t get hung up on price.
The saying that “you get what you pay for” has never been truer than in the mobile dev industry. A huge mistake that a lot of companies have made was selecting vendors who proposed the lowest prices. More often than not, those apps did not perform as desired and business goals were never realized. Make sure the mobile agency you select fits all the other criteria, and then discuss pricing.
7. Ask for a demo.
Even if the app is custom, always ask for a demo of an existing app that is similar to the project you want to be completed. This is the easiest way to determine the quality of the apps that could be developed for your company.
8. Ask a lot of questions.
This seems like a no-brainer, but failing to ask lots of questions was a common mistake made by companies that paid for apps during the initial mobile app frenzy. In an effort to save money by going with the cheapest vendor, these companies instead wasted money on apps that didn’t meet their needs. In the long run, they spent more on app development than they would have had they chosen the best agency for the job instead of the cheapest. Bring in all the internal stakeholders and come up with a list of questions to ask the vendor to make sure no details are left out, which could be detrimental to the project down the line.
9. Do they know your industry?
Mobile agencies that understand your industry and business are invaluable. Instead of just taking orders and accepting the requirements, look for a firm that can challenge your own ideas and provide insight that you may not have thought of before. If they are experienced, they should know plenty about how certain apps work within your business and be able to provide best practices for the project.
In conclusion, after taking everything on this list into consideration, you should be able to narrow down the mobile development firm that is right for your project. Even if your company has had a bad experience in the past, following these guidelines should help you avoid wasting money on an app that in the end does nothing to push the objectives of your business.
Ready to get to know the Shockoe team? Reach out to us and see if we’re a good fit for your next app development project.
While we spend most of our efforts helping clients, there are times where we step back and reflect on the lessons we learn through these endeavors. I spent half of 2017 working with Crown, a leading innovator in world-class forklift and material-handling equipment. Through the course of this time, I personally saw changes confirming the app we were developing truly was a key factor in an increase in their employee productivity.
Through app usage, Crown developed a productivity mindset and removed organizational obstacles to their workforce productivity. The app gives employees the ability to work efficiently, keep their equipment operational, and ensure that tools or parts are readily available. Employees are now more productive because the former structures and processes, that consumed valuable time and prevented them from getting things done, have been replaced. Now, with higher labor throughput and with the same amount of relative work, they are more productive.
With these efforts in mind, I compiled the following five ways an app can increase a manufacturer’s employee productivity.
1. Reduce movement to optimize task efficiency
There are many factors that can contribute to unnecessary, time-consuming movement including ineffective floor layout; temporarily displacing material, information, tools, or people; and inefficient working methods. Movement can be reduced by strategically placing objects and information within an app, giving employees quick and easy access to this information. This can eliminate the need for time-consuming searches and demonstrations. For example, video of how to operate equipment can help employees better familiarize themselves with key information about the operations, which will empower them to make informed decisions that help improve their overall productivity.
2. Improve scheduling and plan for interruptions to reduce bottlenecks
Companies must act quickly when something goes wrong, or when their process must be put on hold momentarily because of a malfunction, rejections, or any other changes that may occur. By having access to real-time information regarding employees, tools, and materials, adjustments and accommodations can be made for interruptions. Establishing the right system enables a company to determine the feasibility of scheduling requests, estimate the impact, and even minimize the impact it could have on production.
3. Improve equipment reliability
Neglecting to maintain equipment, tools, or software puts the process at risk from unaccounted-for downtime. Furthermore, equipment that is poorly maintained or outdated will affect product quality. By taking a more strategic approach and analyzing performance data for key trends, potential issues can be anticipated and maintenance schedules created to extend the longevity of tools, equipment, and software. An app that displays these maintenance schedules gives employees quick access and keeps them informed on equipment status, enabling them to know which equipment needs repairs and which parts are needed for the equipment beforehand. As a result, there will be plans in place to help avoid disruptions to production due to unplanned downtime.
4. Optimize inventory levels to reduce shortages
It’s difficult to be productive when the proper tools to handle a task are unavailable. Companies need to account for and address short count, unexpected delays, and/or late deliveries. An app with this useful information allows accurate and timely visibility of inventory, keeps users informed on what’s running low, possible issues that might arise, and helps address these issues before they become problems that will affect production. In the cases where the shortages are unavoidable, having this system in place will enable users to account for them and even re-assign resources in the meantime.
5. Automate the process
The advancements in robotics, artificial intelligence, and machine learning has reached, or in some cases surpassed, humans in several different work activities. Having an automated process in production, or even part of an existing process can greatly improve the efficiency and productivity of the process. When the gathering and sending of information is automated, the possibility of human error is eliminated, which effectively prevents disruption to workforce productivity.
At Shockoe, we have been helping businesses increase their productivity by implementing these ideas. We even improved our own process by having systems in place to make our process more productive and efficient, so we can deliver an exceptional product to our clients. Our work with Crown has given us insight on how an application can improve a manufacturer’s productivity. By providing functionality like time tracking, inventory and equipment management, parts logs, order checklists, and more, we have successfully improved productivity for Crown’s workforce. Contact us to take the next step toward improving the quality of your company’s processes and productivity today.
On December 6th, we continued our panel series, this time focusing on the Manufacturing Industry, specifically Industry 4.0. Joined by Phil Naglieri (Director of Technology at Shockoe), Mason Brown (UX LEad at Shockoe), Mike Upchurch (Chief Strategy Officer at Notch), and Will Middleton (CEO at Cloudy Data Systems) we explored the results of the Fourth Industrial Revolution – including predictive maintenance, improved decision-making in real time, anticipating inventory based on production, and improved coordination of jobs and people.
We are currently in the Intelligence Age or Age of Information – The Fourth Industrial Revolution, revolution measured around manufacturing, but really on the impact of everything around us. The one we are currently living is characterized by data, analytics, and the merger of technology with the physical, digital and biological worlds.
A Brief History of the Previous Industrial Revolutions
#1 – Agrarian to Industrial (Textile and Industry) & Steam: This revolution took place in during the 18th and 19th century. It was a period marked by the creation of the iron and textile industries as well as the Steam Engine.
#2 – Electricity, Assembly Line, Light Bulb, and Telephone: The second revolution started in the late 18 hundreds and lasted through the beginning of WWI, this revolution was marked by the creation of the combustion engine, the light bulb, the telephone, and the assembly line.
#3 – Nuclear Power, Computers, Computing, and Internet: About half a century later, and really the only revolution any of us lived through is the third revolution, which appeared with the emergence of a new type of energy whose potential surpassed its predecessors: nuclear energy. This revolution also brought with it electronics and the internet—such as the transistor, microprocessor, and computers and the world wide web.
Question and Answer with the Panelists:
Can you give me some insight into the following statement:
“Manufacturing workers are retiring in droves, with an estimated 2.7 million jobs being vacated by 2025. At the same time, the growth and advancement of the industry is expected to create an additional 700,000 jobs for skilled manufacturing employees over the next decade. As a result, manufacturers are scrambling to fill this knowledge and skills deficit with the next generation of workers — millennials.”
Answer (Phil): Mobile is essential to Manufacturing Companies, who are not naive to the process of hiring new generations to fill the roles left by aging workforces as we’ve seen happen in the recent past, Mobile brings a sense of familiarity and allows for quicker adoption. Not only will employers onboard new employees quicker, it will allow them to streamline their processes better.
Question: AI and machine learning are getting a lot of press so can you tell us a little about it? Specifically, as it relates to Manufacturing, where possible
Response (Mike): At a high level, think of AI and machine learning as that you are using machines to do what a human would do if they had unlimited time and capacity. So for example, let’s say you are the production manager at a plant and you are trying to improve yield. You’d look at a bunch of process and machine data in reports, make changes and then evaluate the impact of your change. Machine learning will do the same thing except use math to look at thousands of variables and their interrelationships. The other thing to know is that 80% of the work to use machine learning with be data acquisition and management. To be good a machine learning, you have to be good at data. Finally, the process is iterative and exploratory. For example, a project might start with a question like, “of the 3,000 points of data we capture, what combination of factors cause defects?”. To solve it the data scientist will try different sets and types of data as well as different models to figure out what combination yields the optimal insight.
Question: With the recent addition of bitcoin to the Chicago Board Options Exchange and the Chicago Mercantile Exchange, bitcoin and blockchain are in the news today more than ever. How are these different and is the hype really worth it?
Response (Will): I have been heavily involved in the bitcoin and blockchain space for over a year now and recently became the chapter leader for the Government Blockchain Association Richmond Chapter. Bitcoin and blockchain have been a wild ride this year and the hype is most definitely worth it. The technology provided by the blockchain and the decentralized value exchange of bitcoin are both extremely transformational and disruptive.
Blockchain is one of the underlying technologies behind bitcoin. Though public and private key cryptography, it allows different entities (i.e. an organization, a person, or even a machine) to prove that it is the owner of some data stored on a public database. In Bitcoin, the user can prove they are the owner of the account that sits on the public ledger.
Question: Earlier you talked about machine learning can you tell us how it’s being used in manufacturing?
Response (Mike): There are three common categories of use – predictive maintenance, improvements in things like yield, capacity, and quality, and systems optimization.
Using machine learning for predictive maintenance has proven to reduce downtime, in some cases as much as 50% and increase machine life by 20% to 40%. An example would be predicting part failure and fixing the issue before it happens.
Improving yield/throughput/capacity and quality – studies have shown a wide range of results. In some industries, the increase can be in the 10% range, but in others, like semiconductor manufacturing, where they are already good at yield, the results can 1%. However, in that business, a 1% improvement in yield is worth $100M. This is accomplished by looking at the end-to-end process and understanding not only how each machine contributes to defects, but also the interdependencies of each machine to each other as well as environmental factors; such a factory temperature fluctuations.
As for systems optimization, think of looking at the entire process from sales through manufacturing and delivery. An example would be using 1,000 variables and 10,000 constraints to figure out how to optimize system performance. The company that did it raised earnings 50%. Quite dramatic. A lot of simulation is used here. An example would be that large oil and gas companies have simulations of their entire plant so they can do things like see how changes in maintenance schedules affect the entire system using software and then optimize the schedule before doing any physical changes.
What are the challenges?
- Security – fog/edge/local, not cloud
- Operational – ready to adopt?
- Finding talent