Does your grand plan lack a data foundation?

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Soon after a new data scientist or analyst starts work, we like to check-in on how they are doing. Are they learning new things? Do they understand what’s asked of them? Is the boss happy? Although most thrive and grow, we do also hear of problems in what they expected to be ‘new job paradise’.

Talking with their leaders, we sometimes hear a story of frustration on both sides. Too often the reason for this comes down to data. Rather than enabling this fresh new face to make a difference, data problems can also leave both them & their boss frustrated with the lack of progress.

Our clients will know better than us. But we want to share with you what some have learnt the hard way: Don’t start to build your data science, analytics or insight team without a data foundation.

Even in today’s world of Hadoop, NoSQL or other IT tools (which help you avoid waiting for a huge data warehouse project) there are pre-requisites. Data Scientists can bring hacking & data manipulation skills. But, they too can be held captive.

So, what have we learnt from clients who had to work through these frustrations? Three problems appear the most common:

Barrier 1. Lack of data access

Barrier 2. Lack of data quality

Barrier 3. Lack of data

It might sound childishly simple, but an analyst or data scientist can’t help you if they aren’t allowed access to your IT systems. Most companies don’t want to employ people who have to hack their way in. But today’s alarm about data governance and privacy risks can mean your systems look more like Fort Knox than a data playground for your analyst. Too often we have heard analysts waiting weeks, or months, before getting the access they need. What have we seen our best clients do to avoid this?

Tip 1: Pre-plan:

Involve senior business leaders in your strategy and planning. Early in the process, discuss with them what your team will need. Many IT specialists are interested in the growth of data scientist roles and the potential for Big Data. It sounds like our wisest clients engage them with this topic and ask for their help in making sure the right access is available from day one.

Even when your new hire has access to the systems you think they will need, they may find rubbish there. Particularly for businesses new to the challenge of using analytics, we hear horror stories of inaccurate, inconsistent and incomprehensible data. There can be a misconception that your new hire will just sort all this out. But no amount of coding or statistical skills will help them understand how your business really operates, nor what was intended when that data item was first captured.

Tip 2: Work with data management team:

Although sorting out data quality management can feel less exciting for those wanting to focus on ’sexy’ analytics, this work is vital. Some clients have told us how much it paid dividends to join forces with the data team for the induction of new analysts. Job shares, or shadowing, helped a new hire understand your data better & provide some extra resource to improve known data issues.

Given the amount of press coverage on Big Data and Data Science, it’s perhaps not surprising that some businesses are premature in hiring. We’ve heard of companies that hired a ‘data scientist’ so they could catch-up with their competitors. Sadly, this person then discovered there were no databases or consistent data capture. They had to explain they could not work miracles. Hiring an analyst without having sufficient data is like hiring a salesman when you have nothing to sell.

Tip 3: Be sure who you need:

Chatting with a client, prior to helping them recruit the right people always helps. Sometimes these chats help us both identify that, rather than a statistician or data scientist, what they really need is a data analyst or data engineer. Someone to come in and set-up their data infrastructure before it can be mined for gold.

I hope those tips help you. Checking out your data prior to deciding who to hire is often the right place to start. It’s akin to making sure the foundations are in place before you starting building your home.

Does that ring true for you? Are you investing in analytics skills? Do you have the data teams you need to build that foundation? If you’re not sure and would value a listening ear, to check you’ve thought this through, feel free to get in touch with me here. – We are now recognised as one of Europe’s leading Data Science, Big Data, Analytics and Technology Recruitment and ‘People Solutions’ business. – MBN Consilium (Consilium) is a young but leading insight and analytics consultancy.  Based on experience, client engagements and thought leadership of the people behind the award winning people solutions business, MBN, Consilium is an outcome focused insight strategy consultancy.