Spreadsheet Woes – Limited Features For Easy Adoption of a Control Framework

Like it or not, regulations are here to stay and for a company to comply with them, its IT and financial systems will have to be equipped with a suitable control framework. One common stumbling block to such an implementation is a company?s over-reliance on spreadsheets.

Why is it so difficult to adopt controls for a system that’s reliant on spreadsheets? To understand this, let’s pinpoint some of the strongest, most powerful attributes of these User Developed Applications (UDA).

By nature, spreadsheets are the epitome of simplicity: easy to develop, easily accessible and easily altered. All computers in your workplace will most likely have them and everyone in your organization may be sharing them, making their own versions, and storing them in personal folders.

Sad to say though, these strengths are also control weaknesses and constitute the very reasons why spreadsheets require effective risk management.

Easy to develop. Being easy to develop, most spreadsheet systems are created by non-IT users who have limited knowledge on best control practices. Being constantly under time pressure, these ?developers? may also relegate documentation, security, and data verification to the back burner in favour of coming up with a timely report.

Easy to access. Information in a spreadsheet can be opened by practically anyone within the organization?s network. Who accessed what? And when? If anything goes wrong, it would be difficult to identify the culprit, and the failure to pinpoint responsibility for erroneous data could lead to bigger, more costly mistakes.

Easy to alter. Lastly, if the information is easy to access, then it can also be easily altered, consequently making reports more prone to both accidental errors and fraudulent modifications.

The rise of multimillion dollar scandals due to accidental and intentional spreadsheet errors have prompted regulatory bodies to publish guidelines for mitigating spreadsheet-associated risks. These controls include:

  • Change control
  • Version control
  • Access control
  • Input
  • Security and data integrity
  • Documentation
  • Development life cycle
  • Backup and archiving
  • Logic inspection/Testing
  • Segregation of duties/roles, and procedures
  • Analytics

In theory, these controls should be able to bring down risks considerably. However, because of the inherent nature of spreadsheets, such controls are rarely implemented effectively in the real world.

Take for example Security and Data Integrity. One of the most common causes of spreadsheet error is due to ?hardwiring?. This happens when values are inadvertently entered into a formula cell, naturally changing the logic of the spreadsheet.

As a way of control, cell locking can be applied on the formula cells to prevent users without the proper authority from making any changes. However, when reporting deadlines approach drawing spreadsheets to the forefront of data processing, more people are given access rights to the locked cells. Ironically, it is during these crunch times, when errors are most likely to happen.

Because the built-in features of a spreadsheet support none of the controls mentioned above, some companies are tempted to purchase control-enabling programs for spreadsheets just to continue using them for financial reporting. But although these programs can integrate the required controls, you?d still be interacting with the same complex and outdated interface: the spreadsheets.

Thus, these band-aid solutions may not suffice because the root cause of these problems are the spreadsheets themselves.

Learn more about our server application solutions and discover a better way to implement controls.

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What Kanban can do for Call Centre Response Times

When a Toyota industrial engineer named Taiichi Ohno was investigating ways to optimise production material stocks in 1953, it struck him that supermarkets already had the key. Their customers purchased food and groceries on a just-in-time basis, because they trusted continuity of supply. This enabled stores to predict demand, and ensure their suppliers kept the shelves full.

The Kanban system that Taiichi Ohno implemented included a labelling system. His Kanban tickets recorded details of the factory order, the delivery destination, and the process intended for the materials. Since then, Ohno?s system has helped in many other applications, especially where customer demand may be unpredictable.

Optimising Workflow in Call Centres
Optimising workflow in call centres involves aiming to have an agent pick up an incoming call within a few rings and deal with it effectively. Were this to be the case we would truly have a just-in-time business, in which operators arrived and left their stations according to customer demand. For this to be possible, we would need to standardise performance across the call centre team. Moving optimistically in that direction we would should do these three things:

  • Make our call centre operation nimble
  • Reduce the average time to handle calls
  • Decide an average time to answer callers

When we have done that, we are in a position to apply these norms to fluctuating call frequencies, and introduce ?kanbanned? call centre operators.

Making Call Centre Operations Nimble
The best place to start is to ask the operators and support staff what they think. Back in the 1960?s Robert Townsend of Avis Cars famously said, ?ask the people ? they know where the wheels are squeaking? and that is as true as ever.

  1. Begin by asking technical support about downtime frequencies, duration, and causes. Given the cost of labour and frustrated callers, we should have the fastest and most reliable telecoms and computer equipment we can find.
  1. Then invest in training and retraining operators, and making sure the pop-up screens are valuable, valid, and useful. They cannot do their job without this information, and it must be at least as tech-savvy as their average callers are.
  1. Finally, spruce up the call centre with more than a lick of paint to awaken a sense of enthusiasm and pride. Find time for occasional team builds and fun during breaks. Tele-operators have a difficult job. Make theirs fun!

Reducing Average Time to Handle Calls
Average length of contact is probably our most important metric. We should beware of shortening this at the cost of quality of interaction. To calculate it, use this formula:

Total Work Time + Total Hold Time + Total Post Call Time

Divided By

Total Calls Handled in that Period

Share recordings of great calls that highlight how your best operators work. Encourage role-play during training sessions so people learn by doing. Publish your average call-handling time statistics. Encourage individual operators to track how they are doing against these numbers. Make sure your customer information is up to date. While they must confirm core data, limit this so your operators can get down to their job sooner.

Decide a Target Time to Answer Calls
You should know what is possible in a matter of a few weeks. Do not attempt to go too tight on this one. It is better to build in say 10% slack that you can always trim in future. Once you have decided this, you can implement your Kanban system.

Introducing Kanban in Your Call Centre Operation
Monitor your rate of incoming calls through your contact centre, and adjust your operator-demand metric on an ongoing basis. Use this to calculate your over / under demand factor. Every operator should know the value on this Kanban ticket. It will tell them whether to speed up a little, or slow down a bit so they deliver the effort the call rate demands. It will also advise the supervisor when to call up reserves.

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What GDPR Means in Practice for Irish Business

The General Data Protection Regulation (GDPR) is a European directive aimed at ring-fencing consumer data against illegal or unnecessary access. There is nothing to discuss or debate with local politicians, or the Irish Data Protection Commissioner for that matter. As a European directive, it has over-riding power. To obtain an English version, please visit this link, and select ?EN? from the table of languages.

As you reach for your tea, coffee or Guinness after sighting it, you will be glad to know the Irish Data Protection Commissioner has the lead in turning this into business English we understand. The following diagram should assist you to obtain a quick overview of the process we all have to go through. In this article, we briefly describe what is inside Boxes 1 to 12. The regulation comes into force on 25 May 2018 so we have less than a year to get ready.

The 12 Essential Steps to Implementing the General Data Protection Act

1. Create awareness among your people of what is coming their way. The GDPR has given our regulator discretion to dish out fines up to ?20,000,000 (or 4% of total annual global turnover, whichever is greater) so there is determination to make this happen.

2. Become accountable by understanding the consumer data you hold. Why are you retaining it, how did you obtain it, and why did you originally collect it. Now you know it is there, how much longer will you still need it? How secure is it in your hands, have you ever shared it?

3. Open a communication channel with your staff, your customers, and anyone else using the data. Share how you feel about how accountable you have been with the information in the past. Explain how you plan to comply with the GDPR in future, and what needs to change.

4. Understand the personal privacy entitlement of the subjects of the information. They have rights to access it, correct mistakes, remove information, restrict its use, decline direct marketing, and copy it to their own files. What needs to change in your systems to assure these rights?

5. Issue a policy for allowing consumers access to their information you hold. You must process requests within a month, and you may not charge for the service unless your cost is excessive. You may decline unfounded or excessive demands within your policy guidelines.

6. Adapt to the requirement that you must have a legal basis for everything you do with, and to consumer data. You need to be in a position to justify your actions to the Irish Data Protection Commissioner in the event of a complaint. Having a legitimate interest is no longer sufficient.

7. Ensure that consumer consent to collect, use, and distribute their data is ?freely given, specific, informed, and unambiguous.? From 25 May 2018 onward, this consent will be your only ground to do so. You cannot force consent. Your benchmark becomes what the GDPR says.

8. Issue rules for managing data of underage subjects. This is currently under review and we are awaiting results. Put systems in place to verify age. Set triggers for where guardians must give consent. Make sure age is verifiable. Use language young people understand.

9. Introduce a culture of openness and honesty, whereby breaches of the GDPR are detected, reported, investigated, and resolved. You will have a duty to file a GDPR report with the Data Protection Commissioner within 72 hours, thus it is important to fast track the process.

10. Introduce a policy of conducting a privacy assessment before taking new initiatives. The GDPR calls for ?privacy by deign?, and we need to engineer it in. This may be the right time to appoint a data controller in your company, and start implementing the GDPR while you have time.

11. You may also need to appoint a data protection officer depending on the size of your business. Alternatively, you need to add managing data protection compliance to an employee?s duties, or appoint an external data-protection compliance consultant.

12. Finally, and you will be glad to know this is the end of the list, the GDPR has an international flavour in that multinational organisations will report into the EU Lead Supervisory Authority. This will manage the process centrally while consulting national data authorities.

The GDPR is a project we all need to complete. If we are out of line, it is in our interests to get things straightened out. Once everything is in place, the task should not be too onerous. Getting there could be the pain.

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A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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