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Some IT projects will be small and the end result can be reached very quickly. Other more lengthy projects which aim to deliver a lot may take many months or years to implement. Long projects are often very intensive and can quickly erode the enthusiasm and momentum of the project team if not managed correctly. Typically long projects are broken down into several mini prototype runs to test aspects such as installation, data migration, business process, hardware, integration and user acceptance testing. With this approach the tangible business benefits defined at the start of the project are often not realised until the production environment is rolled out at the end of your project. A closer look at the business drivers for the project may unearth considerable benefits which can be achieved in the earlier stages of the project. This may not work for all projects but if a chance exists to add real business benefits early on without causing project overruns why shouldn’t it be done?

A prime example may be a business unit which is in line for new software, does not have a legacy system or data, does not require integration and has simple business processes to map to the new system. Why should this business unit wait several years for the project to end before a week or two is spent getting that business unit what they need out of the project? Furthermore, reviewing the business drivers for that business unit may unearth a considerable return on investment through delivering earlier – a tangible business benefit earlier on in the project! What will that do to the morale of the staff, project team and stakeholders? Buy-in to the project and momentum are two powerful aspects of successful project delivery.

Of course the opposite may be true for the aforementioned example. The business drivers, benefits and risks are assessed and the payback simply doesn’t warrant the effort. The point is to spend some time really looking at business drivers to see whether tangible business benefits can be reached early on and throughout the project. The momentum of a juiced up project team completing and delivering benefits that are welcomed and celebrated through the life of a project can be extremely beneficial on many levels within the team and organisation.

Keep in mind the following when looking for early wins:

• Focus on maximum return on investment and don’t detract from the end goals of the project
• Pick implementation resources well. Better communication skills and adaptability over technical ability will provide more cohesion with the business units
• Communicate well with the project team and stakeholders. What does the earlier business benefit mean to the project, the users and where to next? Keep up the momentum
• Enjoy the win. Delivering better business should be celebrated

Keep the hammer down! Take the lessons and move on while everyone is hot. Project teams and users run hot after success. Also think about putting the item of “not exploring early ROI wins” as a risk item in your next project. Early ROI doesn’t just benefit stakeholders, it juices up the whole team.

Merry Christmas and Happy New Year to all

We have received a huge amount of support from family and friends (clients included of course!) since forming Adapt in May. We have been kept busy with many interesting projects and, looking at our schedule, 2008 is shaping as another big year for both Adapt and our clients. We look forward to delivering for all clients, adapting solutions and building stronger relationships.

2007 wrap-up

Integrated Asset Management System

Gippsland Water is preparing for a very busy 2008. We have been assisting their Asset Management Team in selecting a suitable AMS solution to replace existing systems. Gippsland Water has a large water factory in construction and implementing Plant Maintenance for it is the first stage of the AMS project. This will involve adding several integration points to systems, including SCADA, to automatically trigger planned maintenance activities. The project will then proceed onto reticulation asset management. Adapt Solutions will be involved with all aspects of the implementation to ensure a successful project outcome.

ATMS - Adapt Task Management System

ATMS is Adapt’s first product offering. It was first discussed with New Plymouth District Council (New Zealand) in July this year when we shared our vision of a solution to fit a need we both saw in their business and the industry in general. We have worked through the development and testing of ATMS with New Plymouth D.C. Initially the application will be used for Property Work Management and integrate to existing GIS and Asset Management applications. ATMS is browser based and built in ASP.NET with extensive use of AJAX and JavaScript to improve usability and application speed. During the build we made sure the application could be deployed across business units and asset types without inhibiting functionality or software licensing. We have made it easy for the client to adapt the application to new business units and processes.

Adapt will have product sheets and marketing available early in the New Year. A huge thanks to everyone involved to date both at New Plymouth and in our development team.  

System enhancement and process documentation

The Dunedin City Council Roading Department has had a very challenging year. Adapt worked with DCC to realign their system reporting to their contract specification. The data outputs now match the specification of the road maintenance contract. DCC are also in the process of recompiling their Road Maintenance Contract which will be released for bids in early 2008.  We are assisting them in writing the system process section.

Data

We worked with good and bad data this year and we do not expect this to change any time soon. However, there are encouraging points. We are seeing a more proactive approach to improving data over time - something we touched on in a recent article.

On the data front we have just started a project for Gerard Cody of Timaru District Council. Gerard has facilitated the GPS capture of a large water reticulation network. We are helping prepare the data to a suitable state before it migrates to their AMS system. We’ll keep you informed on how this goes.

There is increasing pressure to make the best use of data: To mould it; extrapolate it; turn it into a tool to predict the future; to create data models that help optimise expenditure, make smarter decisions or make more money. To do this, we’re replacing our Data Collection hat with our Business Intelligence hat.

It’s not hard to analyse data then wave a bunch of outputs and recommendations around. However, before producing output we like to be sure that we understand the data’s origins, current state and on-going improvement plan. We do this for the following reasons:

* If we understand the data then risk is a known quantity. We can then factor risk before implementing any data analyst recommendations.

* As an owner of data we need to know the state of the data today and how its quality will improve over time. This ensures that any data improvement is prioritised to the areas that greatly enhance business operations.

At Adapt we’re often involved with infrastructure asset registers. These data sets can take several years for the client authority to build up. This often means many data collections from multiple sources, including Asbuilt plans, onsite surveys and local knowledge. In some cases the data is passed through several data custodians. All this change highlights the need to set data accuracy and data confidence standards at the very beginning of a data collection. These standards should be easily interpreted and applied by everyone involved with the data. By applying a standard we can determine the data of poorer quality and set appropriate improvement strategies. We also avoid revisiting the same data twice - data gradually improves over time across the whole data set.

Our aim when improving data over time is to place the data into an Improvement Sieve. Hypothetically, the sieve allows good data (high accuracy) to pass freely through it while the bad data (low accuracy) remains in the sieve - simple. The bad data is then matched against the Data Improvement Plan to derive a priority. Priority data is then improved and the overall accuracy level increased.

Data should be passed through the Improvement Sieve on a regular basis. This enables improvement progress to be reported. It also keeps the Data Improvement Plan as the primary focus when prioritising data clean-ups. It is easy to get distracted and work on new data or some other enhancement. The Improvement plan exists to ensure priorities and timelines are worked to. If this occurs the business and operations benefit from improved and more relevant data sooner.

The right preparation is critical before implementing an Asset Management System. The structure and process put in place beforehand can greatly reduce the amount of time it takes to implement an AMS.
The philosophy underpinning an AMS system should be kept simple. The AMS should best reflect your asset information today so better planning decisions can be made for tomorrow. The AMS is one of many tools that can help you achieve then measure your customer levels of service.
Steps must be put in place now to limit the amount of unnecessary information loaded into a new system. You are spending a lot of money collecting data now so you can utilise it to produce projections on asset repairs and replacements. It is vitally important to prepare yourself so when the AMS is implemented you are ahead of the game.
Thinking data will magically import into a new system is a flawed assumption, yet it is often made. There are methods available to manipulate electronic data but these can be risky and take additional time. It is frustrating for companies who have waited a long period of time to get an AMS to spend more time correcting datasets.
Adapt is passionate about people getting the most out of their data quickly. Some small changes now might mean you get to load more accurate historical data into a new system much quicker. Some thoughts which may help:

Stop expecting that a system will fix all the problems in the organisation!

We all use the lack of a computerised system as an excuse for not having our act together with data and process – this procrastination is not limited to asset management systems. We’ve all seen the excuse: “We’ll have a system one day, let’s address it then”. The lack of a system actually provides more reason to put one together.
I like this approach for 3 key reasons:

• It quickens the implementation time when a system is brought.

• It sends a clear message to those around you that you mean business when it comes to asset management - lack of a system shouldn’t halt progress right now.

• It places robustness around data and process.

Decisions will be based on the data in the AMS one day and you will feel more comfortable doing this knowing that your base data is sound.
You should question current processes and ask will a system really fix this or can this process be improved now! Sometimes there are benefits with changing your approach over time rather than in one big hit during implementation time so starting now is a good thing.

Know the GIS

Building your asset registers from the GIS is a great idea but do some homework. The GIS may look complete but when data is prepared to migrate to an AMS it is the bits you don’t see in the GIS that cause grief. The GIS is just like any other data source, which means the good and the bad points are inherited. You will want to integrate to the GIS at some stage so it is very important to understand how assets are represented in it. Common challenges are:

• GIS systems are not typically geared for holding structured asset attribute data. This may mean data validation errors, non-standardised codes, free form text, non-mandatory fields, missing data and inconclusive data.

• The GIS may store pipes and nodes in a different way to what your AMS model does. For example, water mains in the GIS may be split at every intersecting node. Is this connectivity required in the AMS or can the number of records be reduced by splitting water pipes at every valve or intersection?

• Snapping. The connectivity may look great when zoomed out but when you zoom in, the manhole you thought was associated to an incoming and outgoing pipe may start to drift away from the pipes. This is because the manhole or node has not been snapped to the pipes. This is a significant problem when trying to build an asset register from the GIS data as relationships between assets cannot be established if they don’t exist. In this example, it means orphaned assets exist with no relationship to the reticulation.

GIS can be a great starting base for an asset register as the data has often been captured via GPS and may be more accurate than existing hard copy records (if available).
It has strengths and weaknesses like any data source so it is important to be across them. Don’t forget that changing the asset hierarchy or connectivity may drop connectors to other datasets, including maintenance history.

Standards, standards, standards

Every year, money is spent on contractors and students to go out and collect data, manhole inspections, asset locations, condition inspections, valuations, and CCTV data scored to a standard. Every year, the pile of inspection-related data grows....in the corner.
Massive amounts of field data is acquired quickly and then the waiting begins for many companies, wondering what to do with it all.
If the end point for data is not known then it should not be collected. The resource should be used somewhere else. However, if data is collected, the company and the data collector need to ensure that both sides call a spade a spade. Trouble occurs when one side calls a spade a shovel!
We have seen this happen at numerous sites. In the left hand we have a bunch of standard pipe material codes, which have been standardised so they can slot straight into an AMS when it is implemented. But in the right hand we have a contractor out collecting data who has invented their own pipe material code list. This leads to a second data collection exercise – the one inside the office to make the two codes fit.
This may be a dramatic example but it happens. If the data is no good, tag it as low confidence and move on, don’t waste time patching up data that would be dubious at best. Time spent on cleaning data which is incomplete or of low accuracy would be better spent on putting structure around ongoing data collection strategies. Change and get it right from now on.
Start a data management guideline, which can simply detail data collection, data standards, data storage and data exposure. Adapting a formalised approach to data will help avoid collecting the same data twice. Although you might then have data structure in your department, don’t forget that other asset types or business units will want to migrate their business to the AMS at some stage. If you want to draw analysis across the board you should be collaborating with the other business units now.

What is your AMS vision?

Form a strategic vision for what an AMS will and won’t do and what value it will be in one, two and three years’ time. This will help the organisation avoid the trap of thinking the AMS will solve all the asset management issues and processes in 5 minutes. AMS implementations are lengthy projects and often integrate with many other systems. They can be frustrating projects at times if they are stalled waiting for data cleansing. Project owners and sponsors have to know what they’re in for!
An AMS is a tool to capture all the data we know about our assets and the performance of them, in the knowledge that we can manage the assets better in the future for the customer. This is why Adapt places a high importance on collecting robust asset data as this is the core of your AMS. All activities in an AMS centre on the asset register so it’s worth putting some effort in to getting it right.

Happy Implementing from the team at Adapt.