BLOGTRAINING SCHEDULECONTACT
04
14
Aug

Sourcing is Data Retrieval

The 1960’s band, The Velvettes, got it right when they sang: “findin` a good man, girl is like findin` a needle in a haystack (she-doop la la).”

When sourcing candidates through Internet search or from your database, you do not want to come up with an exhaustive list where the target candidates are hidden amongst the proverbial haystack. Instead you want to achieve a high probability match that the candidates identified will have the mandatory and preferred items you are seeking.

Sourcing is data retrieval.

Wikipedia defines data retrieval as: “extracting the wanted data from a database”. I have added the emphasis on “wanted”, as my aim is to filter out the “unwanted” data.

Let’s think about this. As an example lets say A, B and C are mandatory skills and experience, and D, E and F are preferred – the ideal candidate profile to satisfy the hiring manager.

So how would you go about your search?

Well, before we define our search we need to look at the depth (deep or shallow) and type (structured or unstructured) of data we have access to. This will help you define your search tactics.

For the purpose of this exercise let’s keep it simple and say we can execute the following searches: 

  1. Internal Recruitment Database
  2. LinkedIn 
  3. Google

What would you do first?

I would say many recruiters would take option 2 or 3 before 1. I’d always take option 1 first and search my internal recruitment database.

Why?

I’m seeking a high probability match for my A, B and C and D, E and F so I want to start with data that has better control over how it is structured; otherwise it’s a bit of a lucky dip.

Using my internal recruitment database (assuming it’s searchable) I can search database fields, notes, resumes etc… where I have greater control over what data is stored, how it’s stored and how recent or not the data is. This surely gives me greater control when searching. Remember sourcing is data retrieval, extracting the wanted data from a database.

Do I have this control on LinkedIn or Google, the answer is Yes and No depending what I’m searching for but my probability of a high match is reduced.

My second search would be LinkedIn as the data is definitely searchable and fairly well structured, with some limitations depending on the level of LinkedIn user (Free vs. Talent Finder vs. Recruiter) I have. However, I have no control over the depth of data as it relies on the level and quality of information provided by individuals. Luckily, many candidates on networks such as LinkedIn have enough data on their profile to come up in my search. But what if they only had a Job Title, Location and name? This makes life harder, how would you find these candidates?

As a last resort I would execute a Google Search when I have exhausted all possibilities simply because my probability of a high match is again reduced. Data on the internet is often shallow and mostly unstructured (I have no control how it has been put out there!) so it’s more difficult to be certain your search is achieving the best possible results. Again this will depend on what you are searching and your skill in using Google to search.

So back to how you would go about your search.

How would you search for A, B and C and D, E and F?

How would you make sure you miss nothing?

Here is what I would do when searching my internal recruitment database, LinkedIn or the Internet.

My search sequence would be as follows:

Search 1 – A + B + C + D + E + F

Search 2 – A + B + C + D + E - F

Search 3 – A + B + C + D - E + F

Search 4 – A + B + C - D + E + F

Search 5 – A + B + C + D - E - F

Search 6 – A + B + C - D - E – F

I can’t claim the above approach as my own, I’ve been very lucky on a few occasions now to spend time with Glen Cathey and learn how he goes about his sourcing approach.

Every search above will get different results and I have followed a defined process to cover all possibilities. In theory I should miss nothing if I have my search plan correct.

My first search is shooting for the bull’s-eye, if I’m not successful then I start to peel my search back removing D, E and F until I’m at the outer limits of my search..

Remember sourcing is data retrieval, extracting the wanted data from a database.

When searching your internal recruitment database, LinkedIn or a Google, before you start your next search ask yourself the following 2 questions.

  1. Will my search have a high probability match based on the data I’m searching (depth vs. type)? 
  2. Every search you perform will include but also exclude potential candidates so ask yourself how many ways could a candidate express what you are searching for?

Sourcing (Data Retrieval) is all about having the confidence that in your search strategy, you are not missing anything.

As part of Insidejob Advanced Internet Sourcing and Inside Linkedin training program we teach recruiters how you can build a sourcing plan that will form the basis for your searching and increase the probability of achieving a high probability match when searching you can apply when searching your internal database, Linkedin and Google.

Next blog, I will discuss variations of the data (e.g. people use different job titles for the same type of work), and how to include this in your search plan.

 

Comments (80) | Trackbacks (0) | Permalink