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

?

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 ? ?

?

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

?

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

Failure Mode and Effects Analysis

 

Any business in the manufacturing industry would know that anything can happen in the development stages of the product. And while you can certainly learn from each of these failures and improve the process the next time around, doing so would entail a lot of time and money.
A widely-used procedure in operations management utilised to identify and analyse potential reliability problems while still in the early stages of production is the Failure Mode and Effects Analysis (FMEA).

FMEAs help us focus on and understand the impact of possible process or product risks.

The FMEA method for quality is based largely on the traditional practice of achieving product reliability through comprehensive testing and using techniques such as probabilistic reliability modelling. To give us a better understanding of the process, let’s break it down to its two basic components ? the failure mode and the effects analysis.

Failure mode is defined as the means by which something may fail. It essentially answers the question “What could go wrong?” Failure modes are the potential flaws in a process or product that could have an impact on the end user – the customer.

Effects analysis, on the other hand, is the process by which the consequences of these failures are studied.

With the two aspects taken together, the FMEA can help:

  • Discover the possible risks that can come with a product or process;
  • Plan out courses of action to counter these risks, particularly, those with the highest potential impact; and
  • Monitor the action plan results, with emphasis on how risk was reduced.

Find out more about our Quality Assurance services in the following pages:

The Connection Between Six Sigma and CRM

Six Sigma is an industrial business strategy directed at improving the quality of process outputs by eliminating errors and system variables. The end objective is to achieve a state where 99.99966% of events are likely to be defect free. This would yield a statistical rating of Sigma 6 hence the name.

The process itself is thankfully more user-friendly. It presents a model for evaluating and improving customer relationships based on data provided by an automated customer relations management (CRM) system. However in the nature of human interaction we doubt the 99.99966% is practically achievable.

Six Sigma Fundamentals

The basic tenets of the business doctrine and the features that set off are generally accepted to be the following:

  1. Continuous improvement is essential for success
  1. Business processes can be measured and improved
  1. Top down commitment is fundamental to sustained improvement
  1. Claims of progress must be quantifiable and yield financial benefits
  1. Management must lead with enthusiasm and passion
  1. Verifiable data is a non-negotiable (no guessing)

Steps Towards the Goal

The five basic steps in Six Sigma are define the system, measure key aspects, analyse the relevant data, improve the method, and control the process to sustain improvements. There are a number of variations to this DMAIC model, however it serves the purpose of this article. To create a bridge across to customer relationships management let us assume our CRM data has thrown out a report that average service times in our fast food chicken outlets are as follows.

<2 Minutes 3 to 8 Minutes 9 to 10 Minutes >10 Minutes
45% 30% 20% 5%
Table: Servicing Tickets in Chippy?s Chicken Caf?s

Using DMAIC to unravel the reasons behind this might proceed as follows

  • Define the system in order to understand the process. How are customers prioritised up front, and does the back of store follow suit?
  • Break the system up into manageable process chunks. How long should each take on average? Where are bottlenecks most likely to occur?
  • Analyse the ticket servicing data by store, by time of day, by time of week and by season. Does the type of food ordered have a bearing?
  • Examine all these variables carefully. Should there for example be separate queues for fast and slower orders, are there some recipes needing rejigging
  • Set a goal of 90% of tickets serviced within 8 minutes. Monitor progress carefully. Relate this to individual store profitability. Provide recognition.

Conclusion

A symbiotic relation between CRM and a process improvement system can provide a powerful vehicle for evidencing customer care and providing feedback through measurable results. Denizon has contributed to many strategically important systems.?

Contact Us

  • (+353)(0)1-443-3807 – IRL
  • (+44)(0)20-7193-9751 – UK
Monitoring Water Banks with Telemetrics

Longstanding droughts across South Australia are forcing farmers to rethink the moisture in the soil they once regarded as their inalienable right. Trend monitoring is an essential input to applying pesticides and fertilisers in balanced ratios. Soil moisture sensors are transmitting data to central points for onward processing on a cloud, and this is making a positive difference to agricultural output.

Peter Buss, co-founder of Sentek Technology calls ground moisture a water bank and manufactures ground sensors to interrogate it. His hometown of Adelaide is in one of the driest states in Australia. This makes monitoring soil water even more critical, if agriculture is to continue. Sentek has been helping farmers deliver optimum amounts of water since 1992.

The analogy of a water bank is interesting. Agriculturists must ?bank? water for less-than-rainy days instead of squeezing the last drop. They need a stream of online data and a safe place somewhere in the cloud to curate it. Sentek is in the lead in places as remote as Peru?s Atacamba desert and the mountains of Mongolia, where it supports sustainable floriculture, forestry, horticulture, pastures, row crops and viticulture through precise delivery of scarce water.

This relies on precision measurement using a variety of drill and drop probes with sensors fixed at 4? / 10cm increments along multiples of 12? / 30cm up to 4 times. These probe soil moisture, soil temperature and soil salinity, and are readily re-positioned to other locations as crops rotate.

Peter Buss is convinced that measurement is a means to the end and only the beginning. ?Too often, growers start watering when plants don’t really need it, wasting water, energy, and labour. By monitoring that need accurately, that water can be saved until later when the plant really needs it.? He goes on to add that the crop is the ultimate sensor, and that ?we should ask the plant what it needs?.

This takes the debate a stage further. Water wise farmers should plant water-wise crops, not try to close the stable door after the horse has bolted and dry years return. The South Australia government thinks the answer also lies in correct farm dam management. It wants farmers to build ones that allow sufficient water to bypass in order to sustain the natural environment too.

There is more to water management than squeezing the last drop. Soil moisture goes beyond measuring for profit. It is about farming sustainably using data from sensors to guide us. ecoVaro is ahead of the curve as we explore imaginative ways to exploit the data these provide for the common good of all.

Ready to work with Denizon?

Contact Us Today