The trouble with twins

Sadly there hasn’t been much love shown to Data Quality Services (DQS) in the last few releases of SQL Server, and I don’t think there will be in the coming SQL Server vNext release.

DQS is slow, it’s cumbersome, it’s interface is terrible, it’s does not scale well and takes a number of headache inducing workarounds to get it to a level of decent performance.

However it works, and can work well when it does. However as with all things data when it interacts with people it hurts. Some background to the project, DQS is matching people from separate data sources, each without a common identifier or reference across the systems. So we running some matching to on the data. We can add synonyms, so names like David, can be referred to as Dave, or John, Jon and Jonathan, so in the event of one system using one name it will match with the data from the other. 
So in match we can get a level of confidence, expressed in a percentage, in fact the process uses not just the name but a bunch of other factors, date of birth, address and so on. But one thing it breaks down on is a certain type of twins.
What sort? twins with identical, and nearly identical names. 
Identically named twins, surely no one does that? Sorry yes they do. I have encountered and confirmed that there (At least in one area 4 sets) twins named the same, without a middle name to differentiate them.
As for nearly identical names, again yes, for example Jane and Jade, only one letter different. So when matching them it gets a high level of success, in the high 90’s. What to do? The confidence level can’t be changed as it will ignore or create people when it should or shouldn’t.
Ahhhh people!

I want to dislike something!

Update: Since this post was created back in 2014, Facebook have added some new ‘Like’ options

Businesses need data. Data becomes information, and from that decisions are made. Depending on the data that you have will you make a good or bad decision?
In November 2012 a particular brand got over 61 million ‘Likes’, but as high as that figure is, what information and data can we get from it, and can we make an informed decision from it?
Social media platforms can be an effective way of getting feedback, marketing and advertising, but like most of those tools it is only as effective as the way it is used, the assumptions that you make and the questions that you ask. We also have to remember that it is only in the last 6 years that Twitter was founded and Facebook opened up to everyone and the now ubiquitous ‘Like’ button has only been around since April 2010.
The effect of social media on marketing and user engagement has profoundly altered the landscape between the corporation/company and the consumer. Feedback can be virtually instantaneous and hard for the company to manage. This year the Olympic coverage by NBC in America was advertised as ‘good as being there’ but it decried by those watching it, with time delays, little live coverage and pre-recorded segments. The Twitter hash tag #nbcfail went viral, used not just to refer to the Olympics, but other programs on its network and its brand was tarnished. Also in 2012 the short film ‘Kony 2012’ also went viral but in a more positive way and raised the awareness of the child soldiers in a militia lead by Joseph Kony in pats of Uganda, Congo and Sudan.
There have been many high profile incidences of this sort of positive and negative viral feedback, made possible by the ease of use of social networks ability to communicate among its users, but it is also the ease of use that is its fundamental weakness.
As simple test also indicates something strangely amazing …that actual engagement depends on the question, and looks for simple answers to simple questions. In a completely un-scientific test one of our employees posted the following two status updates within seconds of each other on their Facebook profile:

1: What shall we do about the gap between the rich and poor in the world today???
2: Someone just brought in Crispy Cream donuts into the office…Get in!!!!

Which got the first reply? Answer: 2 (with in 5 minutes of posting)
Which got the most likes? Answer: 2
Which got the most comments? Answer: 2

But to be fair, is this a judgement of the subject matter or just their friends?
Using the ‘Like’ button as an example, it is far too easy for the user to click it, and not a good measure of user engagement. Charities in particular have noticed this, it can get a large number of ‘Likes’ for a campaign, but when averaging out the donations to ‘Like’ ratio it can be as low as 10p per like. Data from the ‘Just Giving’ web site, has found that over a 17 day period they found that about 6% of visitors that came to the site from Facebook ‘Like’ links actually donated. It indicates that it is easy to push the button like, but not to engage. Using the ‘Kony 2012’ example, how many people today can say what happened after they clicked ‘Like’
But back to the original statistic at the start… in November 2012 a particular brand got over 61 million ‘Likes’.
What information can that tell us? In this case nothing of real value. You may have figured out the 61 million ‘Likes’ is referring to the 2012 United States Presidential election. It is only when you consider that Barack Obama got 61,170,405 votes (50.5% share) to Mitt Romney’s 58,163,977 (48% share) can you actually make an informed opinion. In this case the population of America is very much polarised politically and no matter who won would, roughly half the people would not like the winner. In effect 58,163,977 people pushed the ‘Dislike’ button for Obama.
It gets even harder when you look at the effectiveness of the marketing campaign. The campaign to re-elect Obama, cost about $930,000,000, or about $15 per vote. Or was it? We have to remember that the most important people were the undecided voters. Those that would have voted Democrat or Republican anyway do not count in the calculation as their votes are given, and no positive or negative marketing would have made an impact on them. In America for the 2012 election about 23% of registered voters classed themselves as Swing/Floating voters. With 39% committed Democrats and 37% committed Republicans as mentioned before who will vote for their party regardless. So to get from 39% of voters to 50.5% actually cost the Obama campaign just over $300 per vote. A back of the envelope calculation of the combined Democratic and Republican campaigns results in a total spend of $639 for each swing voter. These figures are a very rough approximation of the data, but it indicates that in the whole population of voters, only 23% can be classed as actively engaged.
So we can draw a rough idea of the interactions of the user:

1. Expect a low engagement rate
2. Only expect simple answers to simple questions
3. Target your market selectively

Current customer and market research by Adobe has highlighted an interesting feature request. Users want a ‘Dislike’ button. Why? Maybe because the user wants a choice, they want to be able to say ‘No’ this doesn’t appeal to me, maybe just having a ‘Like’ button is a bit corporate sycophantic, to many ‘Yes’ men driving the functions of the business to disaster. How many people would have pushed the ‘Like’ button if Captain Smith of the Titanic had posted ‘Just told the engine room full steam ahead….icebergs be damned!’
So we can add the following to the list

4. Users would like the choice to ‘Like’ things or not

Currently companies such as Starbucks & Amazon are having a bit of an image issue with the British public due to their low payment of corporation tax. What would be interesting to see is a comparison of the ‘Likes’ over this period. Have they gone down? Have they stayed the same? What would also be an interesting thought experiment is to see what would have happened if there was a ‘Dislike’ button. Would a user be more likely to press this option, rather than not respond? If we are measuring results and success accurately then companies need the fullest information that we can get, ‘Dislike’ may help provide that.

MDX and Sum columns

To be honest this post is just to remind myself on how to do stuff!
I was trying to work out the through put of people going through a stages of a program and got stuck on how to SUM a column in MDX.

Current Program
Next Program
No of People
Sum of People
Percentage To Next Stage
Program 1
Program 2
Program 1
Program 3
Program 1
Program 4
Program 1
Program 5
Program 1
Program 6
This is what i was looking for, to see the %age of people moving to the next stages. How did I get the Sum of ‘No of People’? Well I used the MDX SUM function with a AXIS function thrown in as well.
MEMBER [Measures].[Sum of People] AS SUM(AXIS(1), [Measures].[No of People])
So the ‘Percentage To Next Stage’ was easy
MEMBER [Measures].[Percentage To Next Stage] AS [Measures].[No of People] / [Measures].[Sum of People], FORMAT_STRING = ‘Percent’

SSIS – XML, Foreach Loop and sub folders

SSIS normally has out of the box most things you need to get the job done, however sometime a client comes along with a data source that requires a bit of out of the box thinking. In this case a it was a load of ‘csv’ files in a folder, with over 30 sub-folders, each with a file name which turned out to be a time stamp, that contains a snapshot of their infrastructure, The requirements also needed for it to scale, so the client could add other folders with the same sub folder structure for other parts of their infrastructure. So you would have some thing like this:
And so on for 32 other folders
Right not a problem, I just set up an SSIS For Each loop container click on ‘Traverse subfolders’ option and then set out the data connections.

No, sadly the ‘Traverse sub folder doesn’t work like that. Nuts, so after a quick search I found this link at Joost van Rossum’s blog that uses a bit of C# to get the folder list and generate an XML schema with the folder list in it. You can then use the ‘Foreach NodeList Enumerator’ in the Foreach Loop to get the files.

Well sort of, the code on that website only gets the folder structure, not the full path of the file. It was however a good starting point, and looked like it could be adapted to get the full file list, that could be passed on to the data flow logic in the Foreach Container. Now I’m TSQL through and through, my C# is poor, but slowly getting better, however I did mange to hack the code so it got the file list. So here it is, please use, improve and share.

#region Namespaces
using System;
using System.Data;
using System.IO;
using System.Xml;
using Microsoft.SqlServer.Dts.Runtime;
using System.Windows.Forms;
using System.Collections.Generic;

namespace ST_b87894259c434eeca3da339009a06fdf
/// ScriptMain is the entry point class of the script. Do not change the name, attributes,
/// or parent of this class.

// Use this for SQL Server 2012 and above
// Use the below for SQL Server 2008, comment out the above
// [System.AddIn.AddIn("ScriptMain", Version = "1.0", Publisher = "", Description = "")]
public partial class ScriptMain : Microsoft.SqlServer.Dts.Tasks.ScriptTask.VSTARTScriptObjectModelBase

#region VSTA generated code
enum ScriptResults
Success = Microsoft.SqlServer.Dts.Runtime.DTSExecResult.Success,
Failure = Microsoft.SqlServer.Dts.Runtime.DTSExecResult.Failure

// Variables for the xml string
private XmlDocument xmldoc;
private XmlElement xmlRootElem;

public void Main()
// Inialize XMLdoc
xmldoc = new XmlDocument();

// Add the root element:
xmlRootElem = xmldoc.CreateElement("", "ROOT", "");

// Add Subfolders as Child elements to the root element

// Add root element to XMLdoc

// Fill SSIS variable with XMLdoc
Dts.Variables["xmldoc"].Value = xmldoc.InnerXml.ToString();

Dts.TaskResult = (int)ScriptResults.Success;

// Recursive method that loops through subfolders
private void GetSubFolders(String parentFolder)
// Get subfolders of the parent folder
string[] subFolders = Directory.GetDirectories(parentFolder);

var allfiles = DirSearch(parentFolder);

foreach (var filePath in allfiles)
XmlElement xmlChildElem;
XmlText xmltext;

// var directoryInfo = new DirectoryInfo(Path.GetDirectoryName(filePath));

// Create child element "Folder":
// d:\foreachfoldertest\subfolder1\
xmlChildElem = xmldoc.CreateElement("", "File", "");
xmltext = xmldoc.CreateTextNode(filePath);

// Add child element to root element

// This bit gets the file list and adds it to the subfolders
private List DirSearch(string sDir)
List files = new List();

foreach (string f in Directory.GetFiles(sDir))
foreach (string d in Directory.GetDirectories(sDir))
return files;
So that code now gets the full path for the file and adds it to the XML schema so you will end up with something like this:
That gets passed to the Foreach Loop. So now i have this list of files, how do I load them. As a default, each file has a data connection set up based on the example file the client submitted, once the columns and metadata was set up, the connection string could be moved to an expression based on the XML.
So the over all process looks like this, don’t worry it looks terrifying, but it is quite simple!

Here’s a bit of detail around the process
(1) – The C# script is run to feed the Foreach container
(2) – EXP – Get Feeds Filename. This takes the file path ‘E:\SomeFolder\Network\12345678.csv’ and removes the ‘E:\SomeFolder\’ just to return the ‘Network\12345678.csv’ part, as this is used in later steps to move the file to a completed or failed folder, both of which are set as project variables, so we just append the ‘Network\12345678.csv’ part with an expression to correctly move the file to the correct folder, for example ‘E:\Somefolder\Processed\Network\12345678.csv’.
(3) To correctly process the right file to the right data flow task an expression to get the right folder (FINDSTRING(@[User::SourceFolder] , “\\Network\\”, 1) > 0) and precedence constraint (Success) is used to trigger the correct data flow, and of course the data flow data source connection is controlled by the User::SourceFolder variable. The last two steps are as mentioned a move the completed csv file to a process or failed folder, using a Precedence Constraint set to a logical ‘Or’ so after each data flow it moves the file to the right folder. The process will loop and load until it reaches the last one in the XML and then stop. Its a lot more manageable than creating 35 individual packages to load the data and get around the ‘Traverse Subfolders’ issue. After testing It works very well, and the client can add folders with t he same folder structure for other parts of their infrastructure, and the process can accommodate them. The only pain was setting up all the precedance flows!

Deploying SSIS Packages SQL Server 2008

Bit old school, having been spoilt by SQL Server 2012 and the changes to SSIS that brought with it. Deploying stuff in Business Intelligence Design Studio (BIDS) is less user friendly than I recall. Had to deploy about 20 SSIS packages to the SSIS instance, and the import dialog using SSMS is OK for one or two packages, but i wanted to do them all with out repetition. So it was time for old school command line stuff using DTUTIL, which is still around even in the coming SQL Server 2016.
for %I in (*.dtsx) do dtutil /FILE “%I” /COPY SQL;”/SSIS_Folder/%~nI” /DESTSERVER localhost
In this example i’ve already created a folder in the localhost/Stored Packages/MSDB location called ‘SSIS_Folder’, and running a cmd window from the SSIS Package location. Lets break it down:
This bit just loops though all items in the folder that have a ‘.dtsx’ extension, good old ‘for’. ‘in’ & ‘do’. ‘%I’ is just the variable that holds the file name.
for %I in (*.dtsx) do
The next bit is the good stuff, this calls dtutil and copies the package using the variable ‘%I’ to the folder SSIS_Folder to the destination server ‘localhost’
dtutil /FILE “%I” /COPY SQL;”/SSIS_Folder/%~nI” /DESTSERVER localhost
Nice and easy, completes in seconds. If you need to deploy the same files again you can run the command again and it will prompt you to overwrite with a Y/N prompt, to suppress this prompt and automatically overwrite the package add ‘/Q’ (For Quiet) at the end of the command.

Long live the PC

There has been a lot of talk recently of it now being the ‘Post PC’ era, but is it true, is the PC dead? And how does the current move away from PC’s to Tablet have anything in common with the Galapagos Islands?  That last question may be a little bit strange, but it does have something in common as you will see.
The end of the PC is like one of those conspiracy theories about the end of the world, always upon us or just around the corner but never actually happens. Back in the early 2000’s it was imaged that the house PC would be this small black humming box that sits under the stairs and connects to everything. The buzz word was at the time was ‘Convergence’, which was basically your PC, DVD, TV, Game Consoles, Phone & Internet would all be replaced with some sort of super device. But that hasn’t happened as each maker wanted it to ’Converge’ on their device
which has led to PC’s with TV tuners and TV’s with internet access. A couple of things stopped ‘Convergence’, lack of connection standards and agreement between companies. Content was restricted as media creators and distributors refused to release items in different formats to keep costs down, also wanting to supply their content through their own portals. This is changing now with Hulu, Netflix and iTunes providing easy accessible portals across a wide range of devices.
If we look at the basic design of the PC as an example of ‘Monitor, Keyboard, Mouse’ the form factor has tried to change over the past 20 years but fundamentally stayed the same. The movement from the Desktop to the Laptop, kept the same format. The movement to from Laptops to Netbooks was the same, nothing essentially changed with the base configuration. Sure the mouse got changed to a touch-pad pointing device but nothing really moved forward, it just got smaller over the years.
How does this relate to the Galapagos Islands? Well like the PC form factor, the animals such as the Galapagos Finch adapted from one form and evolved into many variants, each exploiting the particulars of their environment.
The IT Marketing people have appropriated the word ‘Ecosystem’ from the Ecologists, but missed other important words they use……‘Niche. In the Ecological and evolutionary world, one size does not fit all as Darwin found with the Finch’s and Tortoises on the Galapagos Islands. They all evolved from a common ancestor and have over time radiated out into distinct types, and in the current PC market this expansion of devices into ‘Niches’ explains a lot. Netbooks are not expected to be made in 2014 as Tablet sales such as the Surface/iPad/Nexus have destroyed the ‘Small & Portable’ Niche that it once held; they have been out evolved and out competed into extinction.
So tablets have successfully filled the Niche that Netbooks once held, but how and why? Well there have been a few things that have helped. The first and most important is the success of the PC itself, where everyone had one and wanted access to the internet, school work, home accounts or games. People have become reliant on the PC as prices dropped and speed, capacity and user friendliness increased. The increase in the speed and capacity was also a hindrance, if you think about the desktop most people do not need an 8 core processor, 8 gigs of ram and 2 terabytes of storage space if all they are doing is checking their e-mails watching YouTube and playing Angry Birds. The Netbook was under powered trying to be a more portable version of the laptop, struggling with screen size and resolution and trying to keep the full size keyboard functions intact. It was cut down in size, but was still trying to be a Laptop offering the full range of functionality.
The second factor is related to the first, and that is a decoupling of the content creator and the contact consumer. Power users will still require more than a tablet to produce good content, they will need more power, more storage, more than the limited functions of a tablet and App combination can provide. Some people do not even need a tablet; a smart phone can cope with day to day use of checking emails and looking up stuff on the web.
The third factor was the development of a specific operating system for Tablets. Keeping with the ‘Ecological’ metaphor, before a great evolutionary leap there are a few dead ends, the best known was the attempt by Microsoft in the early 2000’s to have a Tablet PC, which was basically a laptop with a folding screen and a basic update to Windows XP to make it sort of usable with a stylus. Apples iOS was a game changer, stripping out anything held over from the Desktop versions of the OS and reducing it down to the fundamentals need for touch based devices, and for the consumption of media. Hand in hand with this operating system development has been the movement from the web browsers world, where everything was accessible and linked in your browser of choice to the App centric world. The YouTube app is a great example of this change, the App is designed for the imprecise nature of touch from the ground up with the limits of writing and navigating on a tablet adapted to.
The spread of the ecosystem of devices has impacted on delivery of BI, as now the information that business runs on has further decoupled from the presentation method. We now gather data in our SQL Server Data Warehouse and now connect/deliver to the SharePoint Dashboard, to the Tablet App, to the Smartphone. Each can show the same information but now presented in a way that realises the limitations of the presentation medium. The CEO can check their tablet for the high level figures presented in nice swish graphics and data designed for it. The manager on the move can get bite size chunks of info sent to the smartphone, and the power users in finance can use SharePoint, Excel and Pivot Tables & Cube connections to analyse granular data.
The PC isn’t dead; we have just forgotten what PC means. PC is Personal Computer, and with the spread of devices from the desktop to laptop, to, tablet, to smart phone to….. Whatever is to come…. all that has happened is that ‘Computing’ become more ‘Personal’ it’s now with us all the time, fitting what we need function wise into an accessible form, the PC has become more PC and we suspect that it is going to be with us for some time to come.

Crime and weather a curious insight

I had a few days between projects, so spent the time getting a bit more familiar with Power Query. I have used crime data to animate a Thermal Map in Power Maps before Here. But I was playing around with Azure Data Market to access the freely available data sets, one of which was the UK Met office weather data to look at animating weather using Power Map. Then i had a bit of a brain wave, I had two data sets, that matched time and space and had a look to see if the weather affected crime. The above graph indicates that the number of Anti Social Behaviour incidents follows the temperature. This isn’t a deep statistical analysis, just a quick eyeball of the flow of the graphs but it is suggestive that something is going on for 2012 at least.

What is Big Data?

The party wasn’t a very good one, 75% of them where teachers for some reason, one person who I sort of knew from other gatherings worked for the HMRC and I was trying to avoid his gaze, not for any financial wrong doings I may add, just knowing governments need cash, and the next thing you know that they have made a mistake in my great grandfather’s PAYE stuff, and as governments really need the money and rather go after international tech companies, I’d get it in the wallet for the compound interest of a shillings mistake 120 years ago. The other person I was avoiding was my lovely wife who was giving me that look which was one of (or combination) of a few options.
1) So I guess I’m driving
2) I can’t believe you said that
3) Don’t mention that bit of gossip about you know what to you know who
4) You mentioned that bit of gossip about you know what to you know who
Somehow I had managed to be talking to the only other people at the party who also worked in IT, so it was a bit of casual shop talk for a bit, and the subject of ‘Big Data’ came up, and strangely all three of us had three different definitions of it. I tend to think of big data in terms of volume, tables with billions of rows or objects that need some sort of business intelligence around it.
The other guy was working for a marketing company and was seeing Big Data in terms of social media, and aggregations from a wide variety of websites and un-structured data.
The third was a business analyst and was talking to about Big Data in term of analytics on the volume or types of data.
Weirdly looking at Big Data definitions we were all correct, but me being me I like to think I was more correct than the others. One of the issues that the marketing guy had was processing the data and the strain on development and hardware resources in processing their customer data to find new insights. It’s not a new problem, when starting a project that would end up driving their industry changing store card, Tesco found that their hardware systems where struggling with processing the large amount of customer data. The data volumes where to just too big, but they hired some data experts who told them they could throw away 95% of the data and just use the remaining 5% to found out the shopping habits of the rest of the population. That has not changed in many business areas, but with the drive of targeted promotions and deeper analysis, there is also a need to process all the data and excuse the metaphor, squeeze as much of the juice as possible out of the customer orange.
But the other issue of Big Data is the mix of the types of data, you can have structured and unstructured data in the mix. Most business have structured data that tells them that they sold a product to this customer at this point in time and shipped it at this date. It’s the unstructured data that is the issue for a number of businesses. What is unstructured data? Well it is quite a mix of types, photos, social media posts, documents and other random data that is not normally time and space specific.
Typically mixing those two types of data has always been tricky, structured data is well known as SQL based technology, relational tables for your related data. Unstructured data has been called ‘No-SQL’ getting rid of the SQL concept to some degree, and using more complex languages such as java to query data sources. With the normal marketing hype, ‘No-SQL’ was the SQL killer, all databases would soon be No-SQL but this hasn’t quite happened, as each type of database is being used for the right job, however some companies have found that after implementing a ‘No-SQL’ solution, they returned back to a regular SQL database model. Another thing that has happened with a number of tools sets such as Microsoft SQL Server and Teradata, is that unstructured data has now been brought into the SQL tool sets, so you can query unstructured data just like structured data. (Technically Unstructured data is a bit of a myth, it all has structure, more in a later post)
Strangely companies using the right tool for the right job is not always done. I was once in a meeting were the Chief Information Officer had been talking to a social media expert and was looking to get this brand new social media platform implemented, which had enabled companies like HP, BT, and other organisations reduce their support costs, by offering a social platform were the users could post their issues and get help from the online community. Thus leveraging the fact that 5% of the users on the social media platforms are pathological helpful. However the question put to him stopped the vision from becoming a reality, as it questioned the use of this technology in this company’s customer engagement and market sector. That question was ‘Erm…. Exactly how do you support a sandwich?’
Anyway back to the party, after some lamentations by the other two I saw the answer to their problems in three words Parallel Data Warehouse (PDW). Oh and the Cloud, that’s four words. Normally when something is chewing some data on a computer its one computer querying the database hosted on it. With PDW the data is split among lots of computers (nodes) all doing the bit of data that it holds, then after a bit of aggregation returns the dataset. Or to put it other way it’s like the difference of if it takes one man to build a wall in 3 hours, how long will it take 12 men?
PDW has been called Microsoft’s best kept secret in terms of analytics, and is hosted in the cloud, which has access to loads of nodes on the server farms around the word. PDW can take tables of billions and billions of rows of data and return it a lot quicker than normal SQL Server, it also deals with unstructured data the same way, delivering insight from all types of data. That just one of the benefits, it also has the added benefit of the usual Microsoft Clouds options, of only paying for what you need when you use it.
I told the other two about it, once again proving that the MD should approve my request to change my job title from ‘Senior Consultant’ to ‘Data visionary and information guru who pushes back the boundaries of ignorance’, the glow of being awesome stopped only when I got in the car with my wife on the drive back home!

Warning Business Intelligence

Ten years have now gone by, I can tell the story of how my IT Skills may have made people lose their jobs.

It’s about 2006/07 and I was working as a Customer Service Team Engineering Gatekeeper at what was then Finning Materials Handling. Basically it was a fancy job title for controlling the field engineer’s assigned forklifts and other equipment. The details got updated, I ran reports and generally tried to chat up temps, and anything with a XX chromosome really. Despite being in such a target rich environment I got a batting average of zero.
Not one.

I also sat next to the most excellent Steve Rowlands, who together we had chats and great bant’s.
Anyway, I should stick to the point, as we had acquired another forklift company called Lex Harvey the previous year, we were running two IT systems. One for the Caterpillar equipment (Finning stuff) and one for the Lex Harvey kit (All sorts of tat). What the issue was is that they were separate systems, no communication between the two so it required a bit of a brain melting issue to log even a breakdown for a customer.
Reporting from it was a right pain as it normally took about a day and a half to produce stuff, however I had a few tricks up my sleeve, mainly to automate the process with use of a VBA type script that could record me doing the reports once. Then all I had to do was a search and replace on the dates every week to run the reports. The process then took me about 2 mins, I just left the script to run on both systems, and boom, leaving me more time to check out the temps, ‘Hi how you doing, would you like a coffee? No it’s no hassle, I like my women how I like my coffee… thrown over me’
So one of the days I had nothing much to do, and realised that I could work out the total equipment numbers of all the teams in the UK, and do some analytics around it. Total numbers, ratio of engineers to forklifts stuff like that.
So I exported all the data into Excel 2003 (Feels like old school stuff) and quickly built up some numbers, and sent it on to the Service Area Managers. It went down a treat. The two from the north, whose names I forget but one of the guys looked like the ‘Cigarette smoking man’ out of the X-Files, went nuts over it. The North West one had done something similar, the North East guy (Mulder knows too much) had also done something similar, but one for the Finning side and one for the Lex side. So kudos all round for Mr Lunn for displaying initiative, technical skill and being awesome. I’d been promoted 3 times in 3 years, maybe this would be the path to the next one. We all got together and sorted out a few issues with the numbers, there were a few items no on the systems which one of our customer owned but we sorted out the servicing.
They then presented it to some other people, then tried to take the credit. It didn’t work…. Hahahaha fuckers!
Any hoo… the report got kicked up to higher management, then even higher management, then to the Chiefs, COO, CIO, CFO, and the big man, the CEO.
They loved it, they went nuts for it, I had some senior people come up to me, and say stuff like ‘Great piece of work Jon’, pats on the back and handshakes all round.
It then got serious.
Really fucking serious.
They started asking questions about the fleet numbers, detailed reports on it, and how I came to those numbers. Sure OK, here’s how I did it, showed them my working out, more comments like ‘It’s a great driver for the business’ and ‘It’s really important that the number reflect the reality on the ground’. So I showed them everything. They all nodded and said stuff like ‘Great, we’re very happy with the numbers now’.
Behind the scenes some meetings started going on, serious meetings, with serious questions, about serious decisions.
They dropped the bombshell, they were cutting back the number of engineers in the field and making redundancies.
Shit fuck.
I felt like a right massive C word. I’d worked running engineers in the south, the midlands, but mostly the north east. They liked me, I was chatty, funny and I used to drive a forklift so knew what drivers did to piss them off when it comes to repairing them. So when they all come down for the meetings and HR stuff, they came and saw me, handed me their paperwork, I shook their hands said the usual platitudes.
Felt like an even more super massive C.
Anyway, it turned out I wasn’t the trigger for it, little did I know is that Finning were in talks with another company called Briggs, which would then purchase the forklift division, and I understand is that Finning wanted to make the company a bit leaner and improve the books. I, however, to some degree had helped.
So the company got took over, I got promoted to IT and Technical Analyst – Business Intelligence. However slightly more careful about what reports I ran.