A Small External Enterprise Development Team is Cheaper than Your Own

Time is money in the application development business. We have to get to market sooner so someone else does not gazump us, and pip us at the post. We increase the likelihood of this with every delay. Moreover, the longer your in-house team takes to get you through the swamp, the higher the project cost to you.

Of course, in theory this should not be the case. Why bring in a team from outside, and pay more to support their corporate structure? Even going for a contract micro team ought not to make financial sense, because we have to fund their mark-up and their profit taking. Our common sense tells us that this is crazy. But, hold that thought for a minute. What would you say if a small external enterprise development team was actually cheaper? To achieve that, they would have to work faster too.

The costs of an Enterprise Internal Development Team

Even if you were able to keep your own team fully occupied ? which is unlikely in the long term ? having your own digital talent pool works out expensive when you factor in the total cost. Your difficulties begin with the hiring process, especially if you do not fully understand the project topic, and have to subcontract the hiring task.

If you decide to attempt this yourself, your learning curve could push out the project completion date. Whichever way you decide to go, you are up for paying advertising, orientation training, technical upskilling, travel expenses, and salaries all of which are going to rob your time. Moreover, a wrong recruitment decision would cost three times the new employee?s annual salary, and there is no sign of that changing.

But that is not all, not all by far. If want your in-house team to keep their work files in the office, then you are going to have to buy them laptops, plus extra screens so they can keep track of what they are doing. Those laptops are going to need desks, and those employees, chairs to sit in. Plus, you are going to need expensive workspace with good security for your team?s base.

If we really wanted to lay it on, we would add software / cloud costs, telephony, internet access, and ongoing technical training to the growing pile. We did a quick scan on PayScale. The median salary of a computer programmer in Ireland is ?38,000 per year and that is just the beginning. If you need a program manager for your computer software, their salary will be almost double that at ?65,000 annually.

Advantages of R&D outsourcing

The case for a small externally sourced enterprise development team revolves around the opportunity cost ? or loss to put in bluntly ? of hiring your own specialist staff for projects. If you own a smaller business with up to 100 people, you are going to have to find work for idle digital fingers, after you roll out your in-house enterprise project. If you do not, you head down the road towards owning a dysfunctional team lacking a core, shared objective to drive them forward.

Compared to this potential extravagance, hiring a small external enterprise development team on an as-needed basis makes far more sense. Using a good service provider as a ?convenience store? drives enterprise development costs down through the floor, relative to having your own permanent team. Moreover, the major savings that arise are in your hands and free to deploy as opportunities arise. A successful business is quick and nimble, with cash flow on tap for R & D.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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Disadvantages of Spreadsheets – Obstacles to Compliance in the Healthcare Industry

Most of the regulatory compliance issues we talked about concerning spreadsheets have been related to financial data. But there are other kinds of data that are stored in spreadsheets which may also cause regulatory problems in the future.

In the US, a legislation known as HIPAA or Health Insurance Portability and Accountability Act is changing the way health care establishments and practitioners handle patient records. The HIPAA Privacy Rule is aimed at protecting the privacy of individually identifiable health information a.k.a. protected health information (PHI).

Examples of PHI include common identifiers like a patient’s name, address, Social Security Number, and so on, which can be used to identify the patient. HIPAA covers a wide range of health care organisations and service providers, including: health plan payers, health care clearing houses, hospitals, doctors, dentists, etc.

To protect the confidentiality, integrity, and availability of PHI, covered entities are required to implement technical policies such as access controls, authentication, and audit controls. These can easily be implemented on server-based systems.

Sad to say, many health care organisations who have started storing data electronically still rely on spreadsheet-based systems. Those policies are hard to implement in spreadsheet-based systems, where files are handled by end-users who are overloaded with their main line of work (i.e. health care) and have very little concern for data security.

In some of these systems, spreadsheet files containing PHI may have multiple versions in different workstations. Chances are, none of these files have any access control or user authentication mechanism whatsoever. Thus, changes can easily be made without proper documentation as to who carried out the changes.

And because the files are normally easily accessible, unauthorised disclosures – whether done intentionally or accidentally – will always be a lingering threat. Remember that HIPAA covered entities who are caught disclosing PHI can be fined from $50,000 up to $500,000 plus jail time.

But that’s not all. Through the HITECH Act of 2009, business associates of covered entities will now have to comply with HIPAA standards as well. Business associates are those companies who are performing functions and services for covered entities.

Examples of business associates are accounting firms, law firms, consultants, and so on. They automatically need to comply with the standards the moment they too deal with PHI.

More Spreadsheet Blogs

Spreadsheet Risks in Banks

Top 10 Disadvantages of Spreadsheets

Disadvantages of Spreadsheets – obstacles to compliance in the Healthcare Industry

How Internal Auditors can win the War against Spreadsheet Fraud

Spreadsheet Reporting – No Room in your company in an age of Business Intelligence

Still looking for a Way to Consolidate Excel Spreadsheets?

Disadvantages of Spreadsheets

Spreadsheet woes – ill equipped for an Agile Business Environment

Spreadsheet Fraud

Spreadsheet Woes – Limited features for easy adoption of a control framework

Spreadsheet woes – Burden in SOX Compliance and other Regulations

Spreadsheet Risk Issues

Server Application Solutions – Don’t let Spreadsheets hold your Business back

Why Spreadsheets can send the pillars of Solvency II crashing down

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Saving Energy Step 1 ? Implementing a Management System

There has been much hype down the years regarding whether management is art or science. Thankfully, where people are concerned the pendulum has swung away from standard times in sweatshops in the west. However, when it comes to measuring physical things like harvest per square meter and the amount of energy consumed there is no substitute for scientific measurement, and this implies a system.

Managing energy cost and consumption down is like any other strategy. American engineer / statistician / management consultant W. Edwards Demming may have passed on in 1993. However he was as right as ever when he said:

When people and organizations focus primarily on quality, this tends to increase and costs fall over time.

However, when people and organizations focus primarily on costs, costs tend to rise and quality declines over time.

Demming believed that 90% of organizational problems arise from systems we put in place ourselves. This can be because we are so accustomed to them that we fail to notice when they are no longer relevant. The currently prevailing laissez faire towards energy is a case in point. What is managed improves and what is not, deteriorates. We know this. Let us take a look at how to apply this principle to energy management.

First, you need to get the subject out the closet and talk about it. How often do you do this is your boardroom, and how does energy rank against other priorities? Good governance is about taking up a position and following through on it. Here is a handy checklist you may like to use.

Do we use a consistent language when we talk about energy? Is it electricity, or carbon emitted (or are we merely fretting over cost).

How well engaged are we as a company? Looking up and down and across the organization are there points where responsibility stops.

How well have we defined accountability? Do we agree on key performance areas and how to report on them.

Are we measuring energy use at each point of the business? When did we last challenge the assumption that ?we’re doing okay?.

Have we articulated our belief that quality is endless improvement, or are we simply chasing targets because someone says we should.

A management system is a program of policies, processes and methods to ensure achievement of goals. The next blog focuses on tools and techniques that support this effort.