How to Train Employees on New Technology

Originally published Jul. 20, 2016, updated Oct. 11, 2018.

The best software on Earth is a failure if the team can’t use it.

Support employees throughout the training process by offering technical assistance, providing a variety of reference formats, and fostering a culture of communication and collaboration.

After all the effort of finding the right enterprise software package, negotiating a sale, and supervising installation, the new program is finally up and running. It’s time to relax.

Well… it’s almost time to relax.

Before companies can start enjoying the benefits of their new software, they need to get over the biggest hurdle of integrating technology: training employees. This is a make or-break-moment.

The best program on Earth is a failure if the team can’t use it. In fact, over half of enterprise software initiatives don’t reach their full potential due to low adoption rates.

The problem is that employees tend to push back against learning new software. They’re already comfortable working around the flaws in the existing system, and they get frustrated with the disruption that comes with even good changes.

This sometimes leaves the impression that the old way was better.

Making the training process as painless as possible encourages employees to get behind new software. Read on for a few ways executives can smooth the path for them.

Provide Quality Technical Assistance

Offering technical assistance is the most influential step companies can take to help their teams learn new software.

This should include both initial software training and supplemental references for troubleshooting issues that come up in the early stages of implementation. The impact of technical assistance is undeniable.

The Primary Care Information Project (PCIP) and Weill Cornell Medical College conducted a study of how health practitioners implemented Electronic Health Records (EHR) and found that small practices without sufficient training resources struggled the most with their EHR systems.

Medical practices that received eight or more training and support visits had the highest levels of success.

When interviewing vendors, ask about their after-sale support. Plan to have a variety of resources and technical references that everyone can use for ongoing training.

Focus On What Matters

As much as 60% of software features are never used. This happens so often there’s a name for it: “shelf-ware”.

To some extent, shelf-ware is inevitable. Commercial software developers need to appeal to as many users as possible. They’re constantly adding new features in a quest to widen their customer base and stay relevant.

The resulting software has a host of shelf-ware most users will never touch.

Don’t make the mistake of trying to teach every esoteric function in the program during training. Focus on the 20-40% of commonly-used features and just touch on the rest.

Leverage Influential Users

In every group there are users who adapt quickly to new software. They’re comfortable with technology and like helping others who run into trouble.

Leverage their enthusiasm by designating them as transitional training leaders.

They can solve low-level problems for their co-workers and maintain any reference tools. It helps to give them a small bonus or other incentive, as well.

Address Problems Early

Communication is key when the training is finished and the software goes live.

Even the most experienced companies experience bottlenecks and setbacks when integrating new technology into their workflows. The only way to overcome these challenges is through communication.

Schedule meetings once every week or two where the whole team can share what’s working and where there could be improvement.

Check in with individual employees between progress meetings. Keep the conversation casual and talk to a variety of team members.

Managers, supervisors, support staff, and even outside vendors have unique perspectives that can help identify problem areas.

Once those issues are identified, schedule additional training on a group or using the transitional training leaders. Early intervention keeps frustration levels down, so employees aren’t tempted to go slide back into the old system.

Use Online Training Materials

Many vendors have extensive training materials on their sites, including videos, walk-throughs, information guides, and downloadable reports.

Self-paced training like this offers another avenue for employees to build their skills and gain confidence in the new software program. Share vendor resources where everyone who works with the software can find them at need.

It’s not always easy to convince employees to use new technology, but the payoff is worth it.

Support the team with quality training options, step in when there’s an issue, and foster an environment of collaborative training. When the employees have the right tools to learn, the project is on the best path to success.

How can your sales, marketing, and finance teams get rid of spreadsheets and become more efficient with their reporting? Download our eBook How to Implement Business Intelligence in Your Company to find out!

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Data Quality Checklist: Is Your Data Ready for Business Intelligence?


To get the most from a BI investment, make sure the data pipeline is in order first.

There’s an old saying that is often applied to analytics: “Garbage in, garbage out.” Results are only as good as the data which feeds them. In fact, preparing that data is 80% of the analytics process. Taking shortcuts with data quality is a fast way to undercut business intelligence efforts.

This checklist is a useful guide for evaluating the existing process and making plans for future infrastructure.

Why is Data Preparation Important?

Data comes in many formats, especially when coming from different sources. When everything is funneled into a communal database there may be blank fields, differences in field labels and numbers, and variations in numerical formats that read differently to a computer (dates are one example of this). Depending on the databases similar records may be duplicated or merged into a single entry.

Messy input like this can produce null or even misleading results. When the data can’t be trusted, it negates the advantage of business intelligence. Data has to be organized into a consistent format before analysis.

Data Quality Checklist

There are five key aspects of good data. To be useful, it should be:


There must be enough data to warrant analysis. All critical fields should be full and there should be an acceptable percentage of non-critical fields filled in as well.


Data should be validated and come from a reliable source. “Reliable” has different meanings based on the type of data, so use good judgement when it comes to choosing sources. Consider who owns or manages the source as well as how the data is collected.


Low cost cloud storage has enabled businesses to store more data than ever before. That can be an advantage- as long as it can potentially be used to answer business questions. Also, check whether the data is still current or if there’s more up-to-date data available.

Consistently structured

Prepare data for analysis in an appropriate format (such as CSV). Data scraped from PDFs and other file types may be in an unstructured state that needs more work to be usable. Follow common text and numerical conventions. Currency and dates, for example, are noted differently in the US versus Europe. Check for duplicates and contradictory data as well; this is a common issue when importing from different sources.


All concerned end users should be able to access the company’s data, providing it’s legal and ethical for them to do so (for example, HIPAA records should be protected). Make sure this can happen in real or near-real time; when staff has to wait days for data requests to come back they tend to move ahead with less informed choices instead.

Make sure there’s a designated data steward who is empowered to maintain the data pipeline. It doesn’t have to be a separate position, but they should be able to speak to company leadership when there’s an issue.

Think in terms of “data lakes” as opposed to “data silos”, too. Data lakes put the entirely of the company’s data in the hands of those looking for innovative ways to improve operations. They can make decisions based on all available information without worrying that some hidden bit of data might derail their plans. (Automaker Nissan has seen great success from this strategy.)

Options for Data Preparation

When it comes to data preparation, the options boil down to manual versus automated techniques.

Manual data preparation is when employees go through data to check its accuracy, reconcile conflicts, and structure it for analytics. It’s suitable for small batches of data or when there are unusual data requirements, but the labor investment is high.


  • Less obvious investment (labor goes up instead of a technology outlay)
  • Low training burden
  • Granular control
  • In-house data security


  • Slow
  • Staff could be working on more high-value tasks which are harder to automate
  • Prone to human error
  • Expensive when labor is considered

With automated data preparation, software is used to sort, validate, and arrange data before analysis. Automation can handle large datasets and near real-time processing.


  • Fast enough to prepare data for streaming analytics
  • Highly accurate
  • Removes labor burden
  • Works on both the front and back end of collection


  • Staff must be trained on the software
  • Initial investment required
  • Working with outside vendors requires extra vigilance for security purposes

Final Thoughts

Data quality may be the least exciting part of business intelligence, but it’s the only way to get reliable results. Take the time to build a strong foundations for your data intelligence process and you’ll be rewarded with more reliable, better-targeted insights.

Having doubts about your data quality? Set up a free consultation with Concepta to assess where you are in the business intelligence process and how to get where you’re going.

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What Does the GDPR Mean for Enterprise?


Something big has changed in the way enterprise handles data, and even customers are noticing. Privacy policy updates have been flooding email inboxes all over the world.

Users log into favorite sites to find pop-ups urging them to review terms and conditions. There are even memes floating around making fun of the phenomenon. For enterprise, however, this is no laughing matter. The General Data Protection Regulation (GDPR) is now live, and companies need to take steps to protect themselves.

This legal framework for managing and protecting consumer data in the European Union went into full effect at the end of May. Companies- even those based outside the EU – who violate the GDPR are subject to steep revenue-based fines. That raises some critical questions for enterprise. What is the GDPR? Who is bound by it? More importantly, how can businesses protect themselves from costly penalties?

Note: This article is meant to be an overview, not legal guidance. A business attorney is the best person to offer specific advice on how the GDPR affects your company.

GDPR Overview

The GDPR was created in response to the rising threats to consumer safety posed by Big Data and evolving IoT technology. It defines data privacy as a fundamental right and puts protections in place for the personal data of European Union residents. That includes things like names, addresses, phone numbers, email addresses, photos, identification numbers, IP addresses, human resource records, and biometric data.

Essentially, the GDPR provides more consumer control over data for EU residents. It applies to people and activity within the EU’s sphere of legal influence, specifically:

  • Residents of the EU
  • Businesses and other organizations based in the EU
  • Entities operating in the EU
  • Entities who collect or process data in the EU or data otherwise covered under the GDPR
  • Monitoring of behavior within EU

There are two categories of entities that are bound by the GDPR. Controllers own and maintain data while processors analyze or process data on the controller’s behalf. Both of these groups are responsible for protecting consumer data, removing the excuse that a company wasn’t responsible for a processor’s actions.

Although this is an EU regulation it has global repercussions. Any company that doesn’t want to implement location-based blocks on data collection from their website or cut off operations in the EU must ensure that data is being protected. The penalties for breaches are potentially high, too. Many international companies are finding it more practical to implement compliance procedures in general to prevent accidental mishandling of EU-related data.

What Changes for Enterprise

GDPR guidelines are simple but wide-reaching, all aimed at putting improving individual data control and peace of mind.

Here’s what changes:


The GDPR affects both any handling data of EU residents anywhere in the world and anyone within EU processing any data. The applicability of data protection laws used to be ambiguous; companies could simply process data outside EU to avoid legal protections.

Consumer control and consent

Individuals have much more control over what happens with their data. They must be told specifically whatis being collected, why it’s being collected, how it’s being used, and what protective measures are in place. There are also exceptions for legal allowances like public safety, a controller’s legal obligations, and the legal data interests of another person. Controllers can’t refuse service for denial of data usage unless data is necessary to provide the service. This set of rights comes with specific additional rights:

  • Access to Data: Consumers can access their data as well as what it’s being used for on request.
  • Data portability: Controllers must provide a data subject with their data in a commonly used format and transfer that data to another controller on data subject’s request.
  • Right to be forgotten (RTBF): Consumers can have their data erased on request both by controller and by any entity who was given the data.

Security by design and default

Controllers must make secure settings the default in all scenarios and take active steps to ensure data security.

Breach handling

Breaches must be disclosed if they could result in any risk to the rights and freedoms of data subjects, including the right to data privacy. Public disclosure must happen with 72 hours of the organization becoming aware of the situation. Processors have an additional duty to inform controllers of breaches on their end without “undue delay” to expedite public disclosure.

Data Protection Officers

This is one of the least understood parts of the GDPR, but it doesn’t need to be complicated. Organizations only need a specific data protection officerin select cases, specifically:

  • When a public authority is processing personal data (except courts conducting official judicial business)
  • When there is regular, systematic monitoring of individuals on a large scale
  • When monitoring certain categories of data including biometric data, data about religious or political beliefs, trade associations, health information, and criminal or legal backgrounds; additionally, this data can only be processed in specific circumstances (ie, with explicit consent of data subject, when legally required)

If an organization does need a designated DPO, there are rules meant to avoid collusion and improve the quality of oversight. The DPO can be a contractor or internal employee so long as their contact information is made available to the relevant Data Protection Authority.

They must be trained on GDPR requirements and data protection best practices. There can’t be any conflicts of interest with other duties or associations. Finally, they have to have complete executive support in terms of training and resources with the ability to report to the highest level of management.


There are standard enforceable fines for violations of the GDPR. Fines are based on different factors (like how much damage was caused, how the issue was discovered, and what the Controller is doing to fix the situation). The basic types of fines call into different categories:

  • Accidents and oversights are punishable by up to the greaterof €10 million or 2% of the organization’s global annual turnover.
  • Carelessness or deliberate violations can cost up to the greaterof €20 million or 4% of global annual turnover.

Protecting Your Company

Here’s a quick checklist of steps that will help companies ensure GDPR compliance and avoid imposing fines.

  • Assess whether the GDPR could potentially apply, keeping in mind that online ordering systems that collect EU data are included.
  • Make GDPR compliance an executive priority. Incorporate the GDPR into onboarding and refresher training.
  • Determine whether a DPO is needed and, if so, make sure they have an unobstructed direct line to company leadership.
  • Identify all types of individual data collected by the company and how it’s used.
  • Minimize personally identifiable data used in general. Good analytics can be done with anonymized or pseudonymized data, so prioritize that.
  • Update privacy policies to spell out data usage, individual rights, and the mechanism for obtaining or deleting individual data records.
  • Review and improve data security measures to include breach handling policies.
  • Recommit to good data management policies(update software, soft target minimization, and so on).
  • Be vigilant for second-hand vulnerabilities like data transfers to non-compliant entities.

Compliance with the GDPR may seem like a hassle, but it’s significantly less expensive than paying for a violation. Plus, having these standards in place benefits companies in the long run by improving public trust and preventing costly breaches.

Deciding whether the GDPR will apply to your enterprise means figuring out where your data comes from and how it’s being protected. Concepta can help. Set up a free consultation with our knowledgeable staff to review your data intelligence process and protect your business from accidental GDPR violations.

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The Easiest Way to Implement Business Intelligence For Enterprise


The benefits of business intelligence are clear to see. Using data makes companies more efficient and highly agile, positioning them to take advantage of opportunities as they arise instead of racing to keep up with the competition.

What isn’t so obvious is how to make the shift towards making data-driven decisions. There are so many BI tools on the market that deciding where to start can seem overwhelming.

The easiest way to stay focused is to build around specific business goals rather than choosing a trendy tool and trying to make it fit. Having a roadmap and a destination keeps business intelligence efforts on track, even when making adjustments as needs evolve.

Every roadmap will be different, but there are some guidelines every company can use to put together a practical, effective business intelligence plan.

Get Your “Data House” in Order

It can’t be said too often that business intelligence is only as good as the data feeding it. Bad data turns into flawed analysis, which leads to wasted time and money.

The first step of any business intelligence project should be conducting a comprehensive assessment of the company’s current data situation. Be sure to include:

  • Data sources available for use
  • Current data management practices
  • Potential stakeholders in a business intelligence project (both major and minor)
  • Wishlist for data or analytics capabilities

The goal is to clarify what the company has now and what would best help push performance to the next level.

This is also a good time to recommit on a company level to good data management. Business intelligence leads to a stronger flow of incoming data, and having familiar policies in place early will help staff take it in stride.

Work in Phases

Set a list of priorities and work in self-contained, cumulative phases to spread business intelligence across the organization. It may be tempting to just start fresh with a whole new system, but there are two compelling reasons to favor a modular approach.


So much goes into launching a business intelligence initiative. The costs go beyond buying or building software. Companies must also consider the cost of integrating it into their existing workflows and improving the data pipelines that feed the analytics.

Starting small both reduces the initial investment and allows the benefits of early projects to help pay for later ones.

Building support

One of the biggest killers of business intelligence projects is a lack of internal adoption. Maybe the product doesn’t fit into existing workflows, or staff aren’t convinced of its benefits.

It doesn’t help that sales teams for BI solutions tend to oversell their software. As a result executives expect too much, too soon, and when the desired results don’t materialize on schedule they become disenchanted.

A phased adoption plan allows the first success stories to build excitement for the business intelligence process. It serves to help manage expectations. Everyone can see how the first project played out and knows what they stand to gain.

Some areas show results more quickly than others, making them better choices for building support. For example, it’s easy to demonstrate the value of email marketing analytics or intelligent customer profiling and lead scoring. Both make staff’s jobs easier while noticeably increasing revenue.

Start with Market Tools

Don’t rush to build business intelligence software from the ground up right away. Needs may be unclear in the beginning; only thorough experience will companies discover does and doesn’t work. It can be frustrating to realize an expensive new suite of software requires an equally expensive overhaul of related workflows.

There are plenty of analytics tools and software on the market to experiment with while getting a feel for business intelligence. Options like Google Analytics, Salesforce, MailChimp, and User Voice offer an impressive suite of tools powerful enough to see real results.

As these prove their worth, companies can have custom software built to organize the various data streams into customized dashboards. These dashboards bridge the gap between the moment when companies are getting all the analytics they need but managing the results is too unwieldy and the point where their needs can only be met with a fully custom solution.

Evaluate, Adjust, Reassess

Schedule periodic assessments to review the business intelligence process as a whole.  Get feedback from all stakeholders, including weighing adoption rates by department to check for inconsistencies that could signal a problem.

Measure performance results against meaningful yardsticks. It’s not enough to say something general like, “Reports increased by 60%”.

Instead, assess the actual impact on productivity and budget with specific instances: Time spent managing leads dropped by 35% while successful sales calls increased by 15%.”

Business intelligence is a dynamic process. Remember to leave room for adjustments going forward. Look back on previous phases to evaluate their long-term value. How are they integrating with new technology? Have they met expectations, or is their performance trailing off?

Don’t be afraid to replace a component that doesn’t work. It’s important to give tools enough time to show ROI, but that doesn’t mean sticking with solutions that are causing problems.

This constant evaluation and correction process is the key to staying on the business intelligence roadmap without getting caught up in costly detours.

What can business intelligence do for you? How can you work BI tools into your workflows in a way that makes sense? To get recommendations about business intelligence software and learn how to organize your data into insights that drive real-world revenue, set up a free consultation with Concepta today!

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4 Habits That Are Holding IT Executives Back


The best IT professionals are passionate about their work. They read trade publications, hang out on forums, and contribute to code repositories and other shared resources.

That passion makes them good at what they do, but it can also lead them astray in the workplace. Sometimes developers become so fixated on their favorite aspects of technology that they make well-intentioned decisions that ultimately hurt the company.

It falls on senior leadership to monitor these IT obsessions to make sure they don’t get out of hand.

Here are some of the worst offenders:

Trend Hopping

Staying on top of the latest technology is part of being a good IT professional, and the First Mover Advantage is real. Investing in promising technology early has the potential to provide a serious competitive edge.

However, some take it too far. These people jump to adopt exciting new trends that aren’t quite market-ready, essentially volunteering their companies as test subjects for unproven technology. If they haven’t done their homework, there could be major issues that negate the first-mover advantage.

The highly competitive automotive industry is an excellent example. In an industry-wide survey, JD Power found that new car owners most often complained about the cutting edge features that were meant to be market differentiators.

Unfortunately, these features weren’t ready for wider use. Voice recognition, which is highly popular and increasingly reliable now, caused a full 10% of new car complaints in 2015. Waiting just a little longer would have allowed the technology to mature enough to meet customer expectations.

There’s another risk with trend hoppers. Without oversight they may discard tools that show promise as soon as (or even before) they achieve a respectable ROI in favor of the “next best thing”. Besides lowering the lifetime value of tech investments, this inhibits the adoption of future projects.

Staff become reluctant to use new technology for fear it will be suddenly replaced. They don’t want to be constantly learning new tools for novelty’s sake; they want to be using the tools that work best. A lack of support can kill even well-planned projects before they start.

To keep trend hoppers in line,  emphasize the need for more than the “cool factor” when considering new technology.

There must be other factors, such as:

  • Issues with the current process;
  • Demonstrated better results with a new solution;
  • Low risk to testing a new solution.

Hanging onto Hardware

There’s beauty in a well-built, well-maintained server room, but insisting on physical hardware can damage a company’s agility. New projects can’t begin development until construction on the necessary hardware systems is complete.

Plus, physical infrastructure requires significant investment. There’s the upfront cost of actually buying, installing, and configuring hardware. Maintenance and security (both digital and physical) raise operating expenses even more.

Equipment naturally becomes outdated and needs replacement. When the company expands, all that equipment has to be taken down, moved, and set up again.

In the vast majority of cases, these are unnecessary hurdles. Cloud storage and computing solutions are maturing into more viable solutions than maintaining in-house hardware for most purposes. They’re easy to set up and come with built-in vendor maintenance.

If the company moves, there’s no hardware to transport or interruption to workflows while technicians get the system running again.

Initial costs with cloud storage are relatively low, too. Companies can buy only what’s needed, then add capacity as required. Ongoing costs operate much like a utility. As a result, software built using cloud solutions begins paying for itself much sooner than its hardwired counterparts.

Data Hoarding

Data has the potential to find or create incredible opportunities. Hoarding data without putting it to work wastes that potential. It costs money together, scrub, store, protect, and maintain data. If it’s not being used, it represents a liability instead of an asset.

That’s what a frustrating number of companies are experiencing, though. 40% aren’t using their data to generate insights, despite spending an average of 20 hours a week gathering it.

What’s behind this hesitation?

  • Options paralysis: There are so many ways data can be used that it’s hard to know where to start.
  • Unusable data: Data is collected but never prepared for use in analytics.
  • Lack of support: Executive leadership isn’t backing adoption of data initiatives.
  • Data silos: Data gets caught in silos where only a small group of people can access it.

When data hoarding becomes a problem immediate, targeted action can shake things loose. Find specific ways to use data, encourage adoption, and leverage those successes into creating a wider data-driven culture.

Using Square Pegs for Round Holes

Sometimes IT professionals “fall in love” with a tool. It works exactly how they like to work, and they want to use it for every possible purpose. They try so hard to make it fit that they overlook a better solution.

The result is unnecessarily complex software and workflows. Even when the favorite tool works for an unsuitable purpose, it takes more time and money to compensate for the bad fit.

For instance, while enterprise apps are wildly popular right now there are some situations in which they aren’t the best  solution. A repair company’s dispatch app could reduce inefficiency in daily workflows, but trying to patch in all partner vendors as well as internal staff would probably cause the app to fail.

Those requirements are too broad for an app, which is meant to provide excellent service over a narrow range of operations.

This can be the hardest habit to break because executives rely strongly on technology recommendations from their staff. In the earliest planning stages of any project, make a point of stepping back and considering several options dispassionately.

Get input from a variety of stakeholders. Make sure the final decision is based on the best fit, regardless of whether it is the coolest tool.


One thing to keep in mind: these habits usually aren’t conscious choices. While they can have serious negative effects, IT professionals don’t mean to damage the company. Their bad habits are merely blind spots.

Executives will get the best results by avoiding a confrontational approach when working around these issues. This philosophy has the double benefit of finding the best solution for the company and helping the developer recognize the potential impact of their habit.

The best way to avoid becoming mired in bad IT habits is to encourage active communication and cooperation within a development team. At Concepta, we have 12 years of experience balancing the strengths and weaknesses of team members during the web development process. To find out how our approach could work for your next project, set up your free consultation today!

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Outsourcing Challenges Around The World


Outsourcing software development is a necessity for businesses who want to get ahead of the technological curve. It’s impractical for a company to create every app and tool necessary for digital transformation efforts in-house, especially not when there are firms with experienced teams ready to tackle those projects for them.

Where many stumble, however, is in choosing which development company to trust with their digital future. Too often price is seen as the most important factor.

It’s thinking like this that drives companies to outsource their software development to areas of the world with favorable exchange rates. For a growing number of businesses, that choice is leading to disaster.

That’s not to say that international outsourcing is always a bad idea. There is a real opportunity to get quality, low-cost software development overseas – as long as companies are prepared to take on the additional challenges that come along with this strategy.

Read on for a look at four popular outsourcing destinations and the unique challenges they present.

Outsourcing to India

Western companies have been drawn to Indian software developers since as early as the 1980s. There are strong benefits to outsourcing to India, though low cost is easily the biggest draw.

Low overhead allows Indian development firms to vastly undercut the standard prices of American or European firms.

The savings arise from how much stronger the US dollar is than the Indian rupee. Right now the US dollar is worth a little over 65 rupees. As a consequence hiring developers is much cheaper.

The average American software developer makes $100,080 annually, but the average Indian software developer earns around 400,000 rupee (or $6132 USD).

Price isn’t the only motivating factor for Indian outsourcing, of course. India has an enormous workforce available for hire.

Around 5 million people across the country list their profession as “software developer” or “engineer”.

Why so many? Those working in the tech industry command four times more pay than those with positions at similar levels in other fields.

The relatively high salaries drive the idea that tech careers are the surest path to a prosperous future. Many of India’s best and brightest learn to code to gain skills that make them more employable internationally.

Working with Indian developers offers options for flexible scheduling as well. The time zone difference between America and India is approximately 9 hours, depending on location.

Indian developers work the bulk of their time opposite American business hours. This is highly conducive to productivity since work will be ready for clients to review and approve when their business day begins.

Challenges of Outsourcing to India

Despite the lower price and large workforce, outsourcing to India carries some very real risks that have become more common over the last few years.

First and foremost are concerns over weak technical skills. There may be a deep pool of available developers, but that doesn’t necessarily translate into the average developer being good at their job.

This is an unfortunate side effect of the disproportionately high salaries in the tech industry. Some young Indians go into software development just to get a good job or comply with family pressure.

They may have little passion for the work. That apathy leads to a lack of innovation and a desire to follow stale routines just to get the job done.

A study by Aspiring Minds, a company that evaluates employability, found that 95% of the Indian developers tested lack the most basic programming skills.

The study assessed 36,000 students from 500 colleges. Less than 5% could write the correct logic for a program, and two thirds couldn’t even write code that compiled.

A mere 1.4% could write solid, efficient code on demand. Weak skills lead to buggy, inefficient software.

Bugs might not be caught before release, either. Some Indian software developers struggle to maintain consistent quality control across the lifespan of a project because of unusually high employee turnover.

That might be surprising given how many developers are looking for work, but it makes sense considering India’s typical benefits structures. Pay starts out higher for engineers than for other fields, then stagnates quickly.

Raises aren’t common without promotions. It’s common practice to leave a position every 2-4 years for another job instead of waiting for a raise that probably won’t come.

Companies find it difficult to remain consistent and keep good quality control when their team is constantly shifting.

Outsourcing to Puerto Rico

Puerto Rico is a hidden gem when it comes to technical talent. It’s been a territory of the United States since 1898 and falls under most federal regulations, so companies there are very experienced with following regulatory guidelines.

Work done there is protected by the same intellectual property laws American companies use.

Many Puerto Rican developers were trained at branches of American colleges, meaning their quality standards are familiar (and high).

The country is close to the American mainland, too. Travelling there to meet with potential partners is inexpensive and relatively short.

The cost of living is lower in Puerto Rico than in the United States. Developers earn around $55,000 annually compared to the American average of $101,000.

Though this isn’t as steep a difference as seen in farther countries, it’s still a considerable discount. The government compliments this with generous tax incentives for companies who outsource.

Challenges of Outsourcing to Puerto Rico

Besides the comparatively lower savings, there are some other drawbacks to using Puerto Rican companies. There are different standards for business ethics at the corporate and government level.

Companies will want to explore those before committing to be sure they’re staying in line with their own operational strategy.

It’s also worth mentioning that the country is prone to hurricanes that sometimes disrupt electrical service. After Hurricane Maria in 2017, two thirds of the country was out of power for an extended period.

It didn’t affect international business as severely as local residents since those companies often had the political pull to get their power back on sooner (or used generators and contingency locations). Still, weather remains a potential risk.

Outsourcing to Bulgaria

Located just north of Greece, Bulgaria has distinguished itself in recent years as a leader in IT outsourcing. It’s ranked first in popularity within Europe and ninth in the world for outsourcing.

Big name clients like Hewlett-Packard, IBM, and CISCO use Bulgarian software developers.

The country’s highly educated workforce is behind much of its appeal as an outsourcing partner. Over half the adult population has a college degree.

Bulgaria has an impressive 99% literacy rate with 45% of citizens speaking at least 2 languages. 85% study English and 25% speak it fluently.

Among the technical community Bulgarian software developers have an excellent reputation for their deep knowledge of programming languages.

While planning for their entry to the European Union the Bulgarian government made regulatory reforms which have standardized some business practices.

These include increased protections for data and intellectual property that were lacking in the past.

Bulgaria lies within a two hour plane journey of most major European capitals. The local cultural traditions are similar enough to their European neighbors to limit misunderstandings between American and Bulgarian companies.

Challenges of Outsourcing to Bulgaria

Bulgaria is close to Europe, but far from the United States. It’s 7 hours ahead of the Eastern Standard Time Zone, which leads to the same kind of problems with communication oversight seen in India or Asia.

Business protections have increased, but they still may be complicated to navigate. For example there is no specific regulation for the outsourcing of IT processes, including for cloud services.

Also, clients are legally liable for actions taken by their outsourcing partners, even without their knowledge. The loose guidelines for outsourcing mean contracts must be exceptionally thorough and specific.

When it comes to savings, Bulgaria is only a little cheaper than America. A Java backend developer can expect to make around $42,000 USD annually.

Wages were lower in the 90s, but the local cost of living is going up as international investment rises.

Outsourcing to Egypt

IT outsourcing is a growing field in the middle East, with Egypt as the most prominent example.

Egyptian colleges and tech schools have a strong focus on IT skills, leading to a larger talent pool than found in other countries in the area. Also, 35% of the general population speaks English.

Price is probably the biggest advantage of working with Egyptian developers. Egypt has the lowest relative cost of living in the world.

Software developers earn an average of 58,270 Egyptian Pounds (or $3,296.33 USD) annually.

Though the cost is low, quality is still good. Egypt’s wide IT talent pool is heavily skewed towards young, educated workers with international-level skills.

The combination of low price and good quality has even drawn branches of major Indian development companies to open branches there.

Challenges of Outsourcing to Egypt

The political situation in Egypt is volatile and has been for some time. That can disrupt projects. There’s also the potential hazard of becoming mired in political red tape cause by the general uncertainty.

Weak intellectual property protection is the second most pressing concern. Egypt technically has laws against IP violations but they’re not well enforced.

The country is on international watch lists for IP violations, which tend to be geared towards entertainment software and pharmaceuticals.

Worse yet, foreign companies generally lack the pull to get government intervention when there are violations.

Being in the Middle East means there are the usual disruptions due to time zones and the difficulty in overseeing operations in a timely manner. Egypt is 6 hours ahead of America, which is just enough to cause problems.

Source: Concepta, Inc

Impact on the Bottom Line

When all things are considered, the lower price of offshore development can be deceptive.

What seemed like a low bid quickly balloons out of control. There are many hidden costs to consider, including:

  • Travel and other costs related to vetting the developer or solving problems
  • Repairing bad code
  • Pricey schedule overruns
  • Opportunity costs from flawed products
  • High maintenance cost of complex software

As a practical note, it’s possible to use a domestic agency to ensure the project gets done within time and budget constraints.

There are several who specialize in a specific region and can serve as regular intermediaries.

This eliminates many of the risks since the actual developer wants to maintain a relationship with the domestic partner and is therefore more motivated to provide better service.

At Concepta, we use carefully screened offshore partners to keep costs low while serving as a “bridge” across the risks. Schedule a free consultation to learn more about this balance between budget and quality.

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