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CIO Talk Network
BI Governance: Making it a reality. ✓ What changes does the new “Normal” require of older governance frameworks? ✓ Who should own or run BI governance?
For more information please visit https://www.ciotalknetwork.com/bi-governance-making-it-a-reality/
BI Strategy
Bi-Survey.com1 conducted a survey in which 2600 BI users participated. 47% of the participants admitted that the right BI strategy helped them make better decisions.However ACI Infotech is a global company delivering next-generation digital services, technology, and business consulting services.For more visit us!
Learn what a successful strategy is, and how to create your plan to deliver a BI strategy that will grow your business!
Business Intelligence is a necessity now as companies cannot survive without gaining critical information about their business. BI analyzes past and current data to predict future trends.
Deploying Business Intelligence for Strategic Decision-Making
Before we dive into deploying business intelligence for strategic decision making, let’s take a look at what business intelligence means. Business Intelligence (BI) is more of a process. It refers to the use of applications, technology, and practices for the collection, analysis, integration, and presentation of business information. It is used to deliver actionable data to executives, managers, and other end-users to help them make informed business decisions.
Business Intelligence involves the use of a variety of tools, applications as well as methodologies to help an organization collect data from internal and external sources. The data is then prepared for analysis, developed, and ran through queries against the data to create dashboards, reports, and data visualization to make the analytical results readily available to the corporate decision-makers and operational workers.
Business intelligence incorporates the use of software and different services to transform data into actionable intelligence. The primary purpose of Business Intelligence is to help corporate executives make better and informed business decisions. It also helps cut costs, spot inefficient business processes, and identify new business opportunities.
Everyone involved in the process of BI has full access to the information to change the ways they work, and that is one reason why sharing is vital to the success of BI projects. The implementation of BI starts with top executives, and the next group should be the salespeople. These are the folks whose job is to increase sales, and they get compensated on their ability to achieve that. Therefore, they are most likely going to embrace any tool that will enable them to do that. So long as the tool is easy to use and they can trust the information provided, they will readily embrace it.
When companies are charting the right course for implementing BI, the first step is to analyze how they make decisions. They should also consider the information needed by executives to facilitate a more rapid and more confident decision making and how they would like the information to be presented to them, for example, as a chart, report, hard copy, online, etc.
BI is a technology project, and just like other technology projects, it can’t yield results if the users are skeptical or they feel threatened by the technology, and they refuse to use it. When implemented, BI fundamentally changes how the company operates and how decisions are made. Therefore, CIOs have to be attentive to the users’ feelings. How does technology affect users and does it increase or reduce productivity?
To Deploy BI Efficiently:
The data has to be clean and the users trained effectively
Deploy it quickly and adjust as you proceed. Don’t spend a lot of time developing the perfect reports because the needs evolve as the business grows. Compile reports that provide the most value at the time.
When building your data warehouse, make sure you aren’t locking yourself into an unworkable data strategy as you go further. It’s best you take an integrated approach to build the data warehouse.
Before you start, clearly define ROI. Outline the particular benefits expected and do a reality check every six months.
Focus on the main business objectives.
When deploying business intelligence in business, don’t acquire BI software because you think you need it. Deploy it with the idea in mind that there are numbers you ought to find out there and roughly know where they might be. Make sure the operational workers, especially salespeople, are okay with the technology before you deploy or it might backfire.
You would be surprised to know that how many companies fail to create a formidable BI strategy. To steer clear from that list, here’s how to improve your BI strategy in just 6 steps!
Toronto Fire Dispatch Data - Real time!
A Wealth of Data on GTA Incidents and Response.
I love finding new (and seemingly untapped) data sources online! While sipping my coffee this morning I found this gem.
The Toronto Fire Services (serving Toronto and all surrounding cities) is publishing live dispatch data to a simple public HTML table. Ripe for the picking. The table is refreshed every 5 minutes with active incidents from the Toronto Fire Computer Aided Dispatch (CAD) system.
There is more information here than you may realize. Let's check it out.
The Active Incidents.
http://www.toronto.ca/fire/cadinfo/livecad.htm
Let's review the table.
Last Updated: Above the table. This is the exact date and time the active incidents were refreshed.
Prime Street: Street of the active incident with a short form for neighborhood / city (i.e. ET = Etobicoke, NY = North York).
Cross Street: Closest cross street to the incident.
Dispatch Time: Date & time the incident was first recorded in the CAD system.
Incident No.: Unique identifier.
Incident Type: Often hyphenated into a main & subcategory.
Alarm Level: High alarm levels are more severe. More units, longer duration.
Area: The Fire Station # assigned to this jurisdictional area.
Dispatched Units: Fleet type and home fire station #. (more to come on this)
As I write this blog post the table data is being refreshed. Every 5 minutes I'm losing quality data! Lets fix this right now. Capturing all the dispatch information is kind of important :)
... Ok, I'm back. I've put together a rather crude process to begin capturing this table. Remember QlikView can easily read HTML tables from websites. I built a QlikView app to load this table. The QlikView app checks the table and incrementally adds this data into a QVD file (compressed data files for QlikView).
I reviewed this great sample QlikView app for geo-coding through Google's API and geo-coded each incident using a combination of Prime Street and Cross Streets (dependent on information available for each incident). Now we have incident latitudes and longitudes in the QVD file!
To capture all the data we need this QV app to reload every 5 minutes. Create a .bat file with a command to reload the document: "C:\Program Files\QlikView\qv.exe" /r "C:\My Dropbox\Fire Service TO\TorontoFireService_Loader.qvw"
Now set Windows Scheduler to call this .bat file every 5 minutes. This works, but it's not a recommended solution. I'm going to write a PHP script to run as cron job on the server and store all incidents into a mySQL database. Watch for the next post.
Now lets look for other information to improve the value of this dispatch data.
Fire Stations
Each fire station is assigned a specific geographic area.
Units will often travel outside this boundary when responding to large emergencies or when specialized units are required, such as High Rise or Hazmat Support. I'm interested in mapping how far units typically travel from their 'home station'.
The station number and postal code is available from the Toronto Fire website. I have compiled this data into a Toronto Fire Stations CSV file available here.
The postal code of every station is also geo-coded by the QlikView script and stored into a supporting QVD file for use on future reloads.
The Fire Truck Fleet
Toronto Fire Fleet information is available on Wikipedia. So what does dispatched unit LA421 mean anyway?
LA is an Air/Light Unit as provided on the Wikipedia page. The digits are the station number. An Air/Light Unit from Station # 421. I made a CSV Reference File for Toronto Fire Fleet units.
We now know the location of the incident, the type of incident, the different units responding and the location of their home-base fire station. Now we're getting somewhere! It's time to load all this great information into QlikView and begin analyzing! I'm looking forward to it.
I would love to hear your thoughts. What kind of data have you discovered lately?
Cheers, Dan.
PS: The Toronto Fire Dispatch System also tweets every new incident to @tofire. Kind of neat. :)
The 5 Stages of Data Denial
Your next data driven discovery will be challenged.
In 2009 I attended a session on healthcare intelligence titled, "Health Data, Indicators and Rankings: What do they matter, what do they measure?" The title itself is catchy - and the content proved quite valuable (and also entertaining at times).
Dr. Brian Postl, CEO of the Winnipeg Regional Health Authority spoke on Winnipeg's approach to leveraging data and driving change. Brain shares, you can't improve unless you change. I would also add that without the data it's awfully difficult to determine that direction for positive change.
Most of the data is used for mythbusting (yes, you can think of it like the MythBusters show on Discovery Channel). In the public sector (healthcare, education etc.) there are endless opinions on performance efficiency - but the cold hard data can settle the debate, right? Data cannot be refuted? Wrong. As I've learned, very wrong. Take a deep breath.
Users love data that supports what they are already doing. So give them some encouraging data they can hug and share. Build their love and trust for your intelligence. The challenge is to leverage data on areas that can be improved - and this is where your results will be challenged. Change often costs money, change is hard, change sometimes means admitting mistakes. In early BI scoping studies I find most departments claim they are the best at what they are doing - especially if funding is driven by performance and there is no intelligence to say otherwise... why not claim you're the best?
Anyone who works with data must understand the following: The use of data can be very devastating for the organization and the community to absorb, especially in a political context. Unfortunately, the only thing reported my media is those ranking below average. "No one shakes your hand for the 80% positive performance, but instead publicize the other 20%," says Brain. I believe data (accurate data) is truth, but do tread lightly and understand the implications of what you discover. Don't be surprised if you're the only one celebrating your find.
In healthcare, data is used for clinical and management accountability. Some nurses love data, they can't get enough of it. Most clinicians are analytically minded. Brain focuses on management accountability, saying they have the greatest ability to influence change in the system - and this is a key application of the data.
Over the past 20 years, every time the Winnipeg Health Region uses data for anything major they go through what Brian calls the 'stages of mourning' (which could be quite funny if it wasn't so damn painful, he noted). I have always remembered the 5 stages of data denial and believe they especially ring true in public sectors where comparisons, rankings, and growing data transparency is open for media and public scrutiny. Here they are!
1. The Data is Wrong
The first response will be, 'Your data must be wrong, that doesn't reflect our performance. There must be a mistake here'. Instead of dissecting and justifying every data element, just ask, 'Is it at least in the ballpark?'. Recognizing the data is never precise enough, there may be something here that everyone can accept - enough motivation to take action and investigate further.
2. The Data is Old
A classic response again. It may not include that last 5 minutes of operational performance, but honestly, how new does it have to be? Ask that question. In the public sector often the data collection itself takes time. Brain mentions that Winnipeg is now close to real-time data, but this question still comes up. Working with real-time data is necessary for true agile intelligence, but may not be necessary for high level trending.
3. We have already changed
That's great news! Now, can we at least demonstrate we've made the changes? At least at this point the organization has acknowledged there was a problem (maybe the data isn't far off after all) and they're trying to improve. Ask what changes have you made? How can we expect to see this reflected in the data? How are we measuring the effectiveness of these changes. All very valid questions to ask when you encounter this 3rd stage of data denial.
4. This is a different place
No one likes being challenged with comparison to a better performing organizing. In my healthcare experience I've learned never to deliver recommendations coupled with comparisons to other health regions without a clear understanding of how the characteristics of each region align. Very often one region will have a different demographic, and this needs to be taken into account.
With that said, how different are they? Help the organization find commonalities that support sharing and application of best practice. Claiming this a different place should not get them off the hook every time.
5. We tried that already
Many nurses, clinicians, teachers and other staff have been asked to change so many times they fear this is just another 'flavor of the month'. It can be hard to convince an organization to try changing, again, to improve performance after their last attempt was unsuccessful. The data might be able to help. With great depth to your intelligence there may be opportunities that were not recognized prior. This a perfect area to leverage a platform like QlikView to dig and explore the data.
LETS BEGIN!
Through this process you need patience, compromise and perhaps most of all, champions! Start with a small change, something you can measure, share and celebrate the success.
So next time you encounter a hurdles along the way, expect the 5 Stages of Data Denial. Plan for them and help everyone through each stage before the real change can begin.
Please leave comments below, share your opinions, your experience, your stories.
You can also connect with me on twitter @dHolowack. (see the Contact page link above)
Cheers.
Love, Data.
