User-Friendly RASCI Accountability Matrices

Right now, you’re probably thinking that’s a statement of opposites. Something dreamed up by a consultant to impress, or just to fill a blog page. But wait. What if I taught you to create order in procedural chaos in five minutes flat? ?Would you be interested then?

The first step is to create a story line ?

Let’s imagine five friends decide to row a boat across a river to an island. Mary is in charge and responsible for steering in the right direction. John on the other hand is going to do the rowing, while Sue who once watched a rowing competition will be on hand to give advice. James will sit up front so he can tell Mary when they have arrived. Finally Kevin is going to have a snooze but wants James to wake him up just before they reach the island.

That’s kind of hard to follow, isn’t it ?

Let’s see if we can make some sense of it with a basic RASCI diagram ?

Responsibility Matrix: Rowing to the Island
Activity Responsible Accountable Supportive Consulted Informed
Person John Mary Sue James Kevin
Role Oarsman Captain Consultant Navigator Sleeper

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Now let’s add a simple timeline ?

Responsibility Matrix: Rowing to the Island
? Sue John Mary James Kevin
Gives Direction ? ? A ? ?
Rows the Boat ? R ? ? ?
Provides Advice S ? ? ? ?
Announces Arrival ? ? A C ?
Surfaces From Sleep ? ? ? C I
Ties Boat to Tree ? ? A ? ?

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Things are more complicated in reality ?

Quite correct. Although if I had jumped in at the detail end I might have lost you. Here?s a more serious example.

rasci

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There?s absolutely no necessity for you so examine the diagram in any detail, other to note the method is even more valuable in large, corporate environments. This one is actually a RACI diagram because there are no supportive roles (which is the way the system was originally configured).

Other varieties you may come across include PACSI (perform, accountable, control, suggest, inform), and RACI-VS that adds verifier and signatory to the original mix. There are several more you can look at Wikipedia if you like.

Check our similar posts

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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What Energy Management Software did for CDC

Chrome Deposit Corporation ? that’s CDC for short ? reconditions giant rollers used to finish steel and aluminium sheets in Portage, Indiana by applying grinding, texturing and plating methods. While management was initially surprised when the University of Delaware singled their plant out for energy assessment, this took them on a journey to bring energy consumption down despite being in an expansion phase.

Metal finishing and refinishing is an energy-intensive business where machines mainly do the work while workforces as small as 50 individuals tend them. Environmental impacts also need countering within a challenging environment of burgeoning natural gas and electricity prices.

The Consultant’s Recommendations

The University of Delaware was fortunate that Chrome Deposit Corporation had consistently measured its energy consumption since inception in 1986. This enabled it to pinpoint six strategies as having potential for technological and process improvements.

  • Insulate condensate tanks and pipes
  • Analyse flue gas air-fuel ratios
  • Lower compressed air pressures
  • Install stack dampers on boilers
  • Replace belts with pulleys and cogs
  • Fit covers on plant exhaust fans

CDC implemented only four of the six recommendations. This was because the boiler manufacturer did not recommend stack dampers, and the company was unable to afford certain process automation and controls.

Natural Gas Savings

The project team began by analysing stack gases from boilers used to heat chrome tanks and evaporate wastewater. They found the boilers were burning rich and that several joints in gas lines were leaking. Correcting these issues achieved an instant gas saving of 12% despite increased production.

Reduced Water Consumption

The team established that city water was used to cool the rectifiers. It reduced this by an astonishing 85% by implementing a closed-loop system and adding two chillers. This also helped the water company spend less on chemicals, and energy to drive pumps, purifiers and fans.

Summary of Benefits

Electricity consumption reduced by 18% in real terms, and natural gas by 35%. When these two savings are merged they represent an overall 25% energy saving. These benefits were implemented across the company?s six other plants, resulting in benefits CDC management never dreamed of when the University of Delaware approached them.

ecoVaro offers a similar data analytics service that is available online worldwide. We have helped other companies slash their energy bills with similarly exciting results. We?ll be delighted to share ideas that only data analytics can reveal.

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