A Business Case for Sharing

We blogged about sharing services in a decentralised business context recently, and explained why we think why these should be IT-Based for speedy delivery. This is not to say that all shared services projects worldwide have been resounding successes. This is often down to the lack of a solid business case up front. We decided to lay out the logic behind this process.

Management Overview ? The overview includes a clear definition of why the current situation is unacceptable, the anticipated benefits of sharing, and an implementation plan were it to go ahead. The project should not proceed until the stakeholders have considered and agreed on this.

Alternatives Considered ? The next stage is to get closer to the other options in order to determine whether an alternative might perhaps be preferable. Substitutes for shared services are often doing nothing, improving the current method, and outsourcing the service to a third party.

The Bottom Line in Business ? Sharing services comes at an initial cost of infrastructure changes, and the impact on human capital (the latter deserves its own blog). The following need careful consideration from the financial angle:

Numbers to Work Through

  • Manpower to design and roll the project out in parallel with the existing organisation.
  • Capital for creating facilities at the central point including civil works, furniture and equipment and IT infrastructure.
  • The costs of travel, feeding and accommodation. These can be significant depending on the time that implementation takes.
  • The opportunity loss of diverting key staff – and the cost of temporary replacements – if appointing line staff to the project team.
  • Crystal-clear project metrics including (a) the direct, realisable savings (b) the medium and long-term effects on profit and (c) where to deploy the savings

Risk Management

Shared services projects don’t go equally smoothly, although planning should reduce the risk to manageable levels. Nonetheless it is important to imagine potential snags, decide how to mitigate them and what the cost might be.

We believe in implementing shared services on a pilot basis in the business unit that eventually provides them. We recommend building these out to other branches only when new processes are working smoothly.

Moving On From a Decision

We recommend you revisit your management overview, the logic behind it, the assumptions you made, and the costs and benefits you envisage before deciding to go ahead

The final step in proving a business case is doable should be fleshing out your roadmap into a detailed operations plan with dependencies on a spreadsheet.

Check our similar posts

Spreadsheet Risk Issues

It is interesting to note that the riskiness of operational spreadsheets are overlooked even by companies with high standards of risk management. Only when errors amount to actual losses do they realize that these risks have been staring them in the face all along.

Common spreadsheet risk issues

Susceptibility to trivial manual errors

Due to the fundamental structure of spreadsheets, a slight change in the formula or value in any of their inhabited cells may already affect their overall output. An

  • accidental copy-paste,
  • omission of a negative sign,
  • erroneous range selection,
  • incorrect data input or
  • unintentional deletion of a character,cell, range, column, or row

are just some of the simple errors spreadsheet users frequently encounter. Rarely are there any counter-checking controls in place in a spreadsheet-based activity and manual errors therefore easily go undetected.

Possibility of the user working on the wrong version

How do you store spreadsheet files?

Since the most common reports are usually generated on a monthly basis, users tend to store them using variations of these two configurations:

spreadsheet storage

If you notice, a user can accidentally work on the wrong version with any of these structures.

Prone to inconsistent company-wide reporting

This happens when a summary or ?final? spreadsheet is fed information by different departments coming from their own spreadsheets. Even if most of the data in their spreadsheets come from one source (the company-wide database), erroneous copy-pasting and linking, or even different interpretations of the same data can result to contradicting information in the end.

Often defenceless against unauthorised access

Some spreadsheets contain information needed by various individuals or department units in an organisation. Hence, they are often shared via email or through shared folders in a network. Now, because spreadsheets don’t normally use any access control, any user can easily open a spreadsheet file and view or modify the contents as he wishes.

Highly vulnerable to fraud

A complex spreadsheet system with zero or very minimal controls provides the perfect setting for would-be fraudsters. Hidden cells with malicious formulas and links to bogus information can go unnoticed for a long time especially if the final figures don’t deviate much from expected values.

Spreadsheet risk mitigation solutions may not suffice

Inherent complexity makes testing and logic inspection very time consuming

Deep testing can uncover possible errors hidden in spreadsheet cells and consequently mitigate risks. But spreadsheets used to support financial reporting are normally large, complex, highly-personalised and, without ample supporting documentation, understandably hard to follow.

No clear ownership of risk management responsibilities

There?s always a dilemma when an organisation starts assigning risk management responsibilities for spreadsheets. IT personnel believe users in the business side of the organisation should be responsible since they are the ones who create, edit, store, duplicate, and share the spreadsheet files. On the other hand, users believe IT should be responsible since they have always been in-charge of managing IT infrastructure, applications, and files.

To get rid of spreadsheet risks, you’ll have to get rid of spreadsheets altogether

One remedy is to have a risk management activity that involves both IT personnel and spreadsheet users. But wouldn’t you want to get rid of the complexity of having to distribute the responsibilities between the two parties instead of just one?

Learn more about Denizon’s server application solutions and how you can get rid of spreadsheet risk issues.

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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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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

Telemetry and the Survival of the Human Species

Without moisture, plants die. Without fodder, the animal food chain collapses. This is why climate change is the greatest threat humankind faces. Crop management needs timely information regarding ambient conditions, and also in the soil itself. In dry areas, online knowledge of trends in rainfall, sunlight, wind speed, leaf moisture, air temperature, relative humidity and solar radiation are indicators of soil stress that can be deadly for plants, and everything that relies on them.

As climate change bites, the need to find solutions accelerates. Drones swoop across to monitor ambient conditions, while probes sunk into plants and the earth in which they grow transmit information to big data repositories for feedback to administrators. In Australia, a remarkable cattle farmer is applying the same approach to his herds.

Nuffield scholar Rob Cook has always been on the edgy side of things. He lost his mobility in a helicopter crash in 2008 patrolling farmland but that has not deterred him. If anything, it has freed his mind to explore the potential that telemetry offers farmers in Australia. He shared this potential with the young beef producers in Roma Australia recently, and here is a summary what he said.

Being wheelchair bound he had to shift from herding with cattle dogs to a more scientific approach. He bought a farm 230 miles / 370 kilometres inland from Brisbane in a warm, temperate climate with significant rainfall even in the driest months. He uses observant software that reports on critical issues like water levels indicating animal consumption, and supplementary water flows from a central irrigation channel.

He also monitors fodder sources for dryer months, and moisture levels in food stocks. Rob is committed to making every blade of grass count. ?We even have the ability to take a photo of the cattle when they are taking a drink of water,? he explains, and that provides valuable information regarding tick and fly infestation and overall condition.

None of this would be possible for Rob Cook without telemetry, which is the process of collecting data at remote points and transmitting it to receiving equipment for analysis. Independent farmers do not have equipment to fund these analytic resources on their own, and use big data resources in a cloud to obtain reports. ecoVaro is on top of current trends. Please speak to us when you need independent advice.

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