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Tag: data project

Be a Data Hero and deliver Net Zero!

Posted on by David Rice

The biggest problem in the WORLD!

It is clear that we need radical changes to save our planet. Governments, the private sector and individuals aspire to achieve ‘Net Zero’ – but radically changing the way we operate is not going to be easy.

Achieving this goal is going to be a huge challenge for big, complex organisations.  There are so many areas to explore, from reducing travel and fossil fuel consumption, leveraging renewable energy, improving efficiency of existing equipment, or simple behavior change.  With so much complexity the task can be daunting. 

Can data save us?…

Starting with data can help you to understand where the quickest and biggest wins are.  This helps you to understand what to focus on first.  As Peter Drucker once famously said “You can’t manage what you don’t measure”.

To create a link between desired outcomes and measurable targets you can use a ‘Data Value Map’. Whilst I love technology and data…it’s only useful when it drives actions and creates positive change.  The Data Value Map helps to visualise how data can help you to achieve your goals.  If your goal is Net Zero…it could look something like this:

Data Value Maps can be achieved using a mind mapping or collaboration tool (I like Mindmeister and Miro) and are best done as a highly collaborative team workshop…don’t forget to bring the coffee and cakes!

Now you have a clear view what data is required to measure and act (your “use cases”) to deliver the Net Zero goal.  Next you can score these in terms of Value and Complexity.  Something like a prioritisation matrix can help:

By focusing in on the ‘high priority’ and ‘low complexity’ use cases you can deliver quick wins to the business.  This will help you to demonstrate you are a true Data Hero and can help your organisation to fly!

Once you have prioritised your use cases, you can start to map out the underpinning systems and processes that are needed to deliver connected, structured data to drive your Net Zero goals. 

Delivering at lightning speed…

There are numerous technologies out there that can help you connect all of this data, but we love Matillion for being able to easily and quickly connect to almost any source and transform and join data to make it useful.  As a data platform Snowflake is fantastic for virtually unlimited storage, blistering speed, data warehousing and data science capabilities.  These technologies will certainly enable you to hone your capabilities as a true Data Hero!! There are also many other fantastic cloud solutions that can help you to supercharge your Net Zero data capabilities.

Join the Data League!

Snap Analytics’ team of Data Heroes are helping one of the UK’s largest food manufacturers to leverage data to drive positive change…but if we’re going to solve humanity’s greatest threat…it’s going to take a whole Justice League of Data Heroes.  So join us on this mission to save the planet, and lets all make sure the decision makers in our organisations have the data they need to drive positive change.  Don’t delay…be a Data Hero today!

We believe that businesses have a responsibility to look after our earth…it’s the only one we have!  We will give any organisation a 15% discount on our standard rates for any work directly linked to making a positive change to the environment!

5 common data project challenges and how to avoid them

Posted on by cre8ion

Any data project is filled with challenges; solving these problems or avoiding them altogether is the key to success. Narrowing this list down to just five was a challenge in itself!

Challenge 1: My data is getting too complicated

Our mantra is ‘keep things simple’. That applies to the amount of code we write as well as reducing unnecessary maintenance and management of technology. Unfortunately this isn’t everyone’s experience. For example, when you’re attempting to integrate a variety of existing systems it presents your average developer with a tempting challenge: ‘I know how to fix this,’ they immediately shout out, ‘but it’s going to take a while!’ Chances are, somebody, somewhere has already solved that exact same problem. Rather than waste time and money reinventing the wheel you can simplify these things by using out of the box connectors and automated data pipelines which allow you to connect to your source systems straightaway. They’re pre-built and remotely managed, so you can be working on your data in minutes not months! 

Challenge 2: Nobody’s using my dashboard

The dashboard is the place to splash your important findings in a way that is accessible and easily understood. So how come nobody is looking at it? It’s a gripe we often hear from stakeholders who’ve asked for the dashboard and the developers who sweat over them. The truth is, you can make the best, most functional dashboard in the world but nobody will look if it’s carrying the wrong information. The solution lies not in greater technical or creative prowess, but during the planning stages of your entire data project. First define the overall strategy and goals for the business and then ask how your data can help reach those goals. Secondly, identify those individuals in the business who are accountable for the numbers and targets. Without clear ownership of numbers and without insights that actually drive action, then why should anyone care what’s on the dashboard?

Challenge 3: The tech team is arguing with the business team

Traditionally there’s been ‘them’, the business team and ‘us’, the IT guys, and communication between the two can be more dysfunctional than a bad tempered debate in the House of Commons. Cross purposes and hidden agendas can make a long term data project a fraught affair, but there is a straightforward solution: nominate one developer with the appropriate people and communications skills to be embedded in the business to act as a single point of contact. This ensures that information and requests get passed on to all the relevant parties in a language they understand and you’ll avoid tedious delays and costly repetition of work.

Challenge 4: My data project is going over budget

This comes back to our golden rule of keeping things simple. Many data firms will spend three months or more setting up infrastructure and installing software before they even begin to analyse data. You needn’t do any of that if you use a data streaming service like Fivetran or a cloud data warehouse like Snowflake. Rather than wait until day 91 of a project you can start integrating data straightaway And the quicker you begin loading and looking at the data, the sooner you’ll start to see results. Beyond this we like to use the agile approach in any project, delivering in regular stages which gives us the chance to make mistakes and reset if need be. As we like to say: fail fast, but fail cheap.

Challenge 5: My data project is taking too long

This is perhaps the number one gripe for many companies involved in complex data projects. The causes are many, and can be solved by successfully overcoming the other challenges on this list. Making sure you clearly understand the requirements up front, and have a clear view of the problem you are trying to solve is key. In addition, we recommend clear planning with measurable outcomes at every stage and employing a good project manager to keep everything (and everyone) on track and to deadline. Find out how our own agile approach to analytics could help you quickly get the data your business needs. 

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How will IR35 impact your data project – and what can you do about it?

Posted on by David Rice

There are many things to consider when running a major data project. Weighing up the long term benefits over sometimes considerable short term expenditure can cause project managers sleepless nights. But come April 2020, many businesses will be asking themselves whether they can even afford to keep their project going. 

The latest factor to consider is IR35, which might sound like a secret branch of the security services, but is in fact a piece of HMRC legislation that will affect many thousands of companies and 230,000 freelance contractors. It aims to deal with the problem of ‘deemed employment’, the practice of using workers on a self-employed basis, often through an intermediary company when permanent employment would be more appropriate. Using these ‘disguised employees’ can save companies considerable sums in tax and National Insurance contributions, and deny workers of employment rights. Under the new arrangements it is up to the employer to assess whether anyone working for them falls within the bracket of IR35. 

On paper this sounds like a fair way of tackling tax dodging and unscrupulous employment practices. But in the public sector where IR35 has already been rolled out many IT projects have been put on hold due to fears over rising costs and investigation by HMRC. Understandably the legislation has caused considerable trepidation across the business world. A survey by Be Digital UK found that four out of ten businesses are considering phasing out contractors altogether. The result of this could see many IT projects grind to a halt.  

What can you do to lessen the impact on your data project? 

The rules surrounding who does and doesn’t fall inside IR35 are rather opaque. There is no one definitive rule, rather a number of questions that you need to answer to assess a contractor’s status. Many employers remain concerned they may still fall foul of the legislation. The most foolproof way of ensuring you avoid the IR35 trap is to make everybody employees. Of course this is a significant long term investment, and could leave you with the additional problem of what to do with them once a project has come to an end. 

Terms of employment 

A key thing to consider is whether the role a contractor fulfils falls firmly within the parameters of the project they have been employed to do. It is often common practice for people to shift around as projects change. Contractors can find themselves on the organisation chart next to regular staff and being moved to different parts of the business. This is definitely not OK under the new rules. 

Milestones 

Project based work, particularly in IT is commonly based on milestones, rather than days worked. Projects billed on milestones are great for ensuring that contractors are clearly delineated as contract workers, rather than slipping into the area of ‘deemed employment’. 

Think big 

Peace of mind can come from working with a large consultancy who can guarantee they only use their own people; this circumvents the IR35 headache for the client. This has been the go to solution for many public sector organisations, but it’s one that comes with a considerable price tag. 

Think small 

You could reach out to smaller IT consultancies, as under the new legislation businesses employing fewer than 50 people and turning over less than £10.2 million annually will be exempt. If they need to hire contractors the rules won’t apply to them. Furthermore, they are likely to offer significantly lower costs than the big consultancy firms and can still deliver great value, especially for specialised pieces of work. 

Undoubtedly the introduction of IR35 will cause anxiety, particularly in the short term, about the viability of certain projects. There is no single best way to deal with the new IR35 legislation and ultimately the right choice for your data project will depend on a variety of different factors, however if you would like to speak to Snap Analytics to see how we can help then please get in touch: 

[email protected]. 

5 things to do before starting a data project

Posted on by David Rice

You’re about to start a big data project. Fantastic! We’re big believers in the fact that every business can gain a real competitive advantage through analysing their data. It’s why we do what we do. 

But just before you go running off all excited, stop for a moment. If you really want your data project to be a success, you need to think about five key things before you even start. 

Understand the problem that you are trying to solve 

Chances are you’re looking to data analytics to fix a specific need, something which is causing inefficiencies and costing you money. Don’t assume though that by shaking the data tree enough times a solution will magically fall into your lap. First you need to look at your existing systems to see what exactly needs fixing. It’s only once you have a clearly defined vision and end point in mind, that we can see exactly how we can help. 

Define what success will look like  

Having identified what you want, it is time to think about what a successful outcome might look like. It helps nobody to embark on a data project without setting any specific goals or measurable outcomes. So make a plan, draw up a list of milestones, devise ways of measuring what’s happening and then track the results against that. One useful approach we’ve found is to run a user survey six months down the line and find out how people are using, or benefitting from the findings.  

Align with company strategy 

It’s all very well you dreaming up fantastic, innovative data driven projects that will change the very fabric of your business and the world generally. But it might be best, first of all, to check that your goals are something that fall in line the wider strategic direction of the business. Is this a problem you should even be solving? Is it a business priority? Will it help tick some important boxes when the annual report comes round? If the answer is yes to all the above, fantastic – you’re on your way to getting managerial buy-in and tapping up a healthy budget for an important piece of work. 

Data for the people 

You’ve addressed the needs of the bigger cheeses but don’t forget about the little guys, the people on the front line who are working hard to produce this data in the first place. Think about how this is going to benefit them in the long term, how will it make their day-to-work work easier, more efficient, or more effective? This is particularly pertinent if your business is going through a restructuring process. We’re great believers in the power of data analysis, but if you’re losing half your team it might not be perceived as the best use of company resources. 

Build the right team 

One commonly held assumption we come across is the idea that data is purely a tech led process: you identify a problem or need and the nerds crunch the numbers. It’s not that simple of course. To produce an effective outcome, you need quality input from people on the business side, members of the team who can provide insights into how the company works and what its goals and strategies are. You should bring together people who use the data in different ways and can provide the broadest possible range of experience. That way the insights we produce will be deeper, richer and ultimately more valuable. 

How to get buy-in for your data project

Posted on by David Rice

Despite the talk of a data driven revolution, the reality for many companies often lags someway behind the ideal of a business built on reliable detailed information analysed using AI. According to a Mckinsey Digital report on leadership and analytics, CEOs cite their biggest challenges to investing in data are “uncertainty over which actions should be taken” and “lack of financial resources.” Fundamentally, it appears that some business leaders still don’t believe that analytics have a high enough ROI.  

If you know that a data project could deliver huge value for your business but you’re struggling to get anyone else to appreciate the importance of all that expensive tech and numbers nonsense, here are a few ways to help change their mind. 

Speak their language 

There’s no point trying to convert anyone into data evangelists at this stage, instead work within the parameters of your organisation. Align your project to existing business priorities and show that you understand the CEO’s strategies. The best way to do this is to create a link between the results of your project and the financial benefits. Get those graphs at the ready! 

Remember that this is a business transaction and not a technical pitch. You’re wasting your time if you can’t convincingly demonstrate that you are addressing a particular business need, so resist using too many technical terms. Instead, explain using visuals which demonstrate that the outcomes from your data project align with the strategic objectives of the business and will bring tangible benefit to the company and the individuals who work there. 

You may need to convince people that you are addressing a demand that they didn’t even know they had. By the end you want not just buy in, but for them to believe that it was their idea all along! 

Recruit key players 

It’s not enough to expect the techies to wave a magic wand and sprinkle stardust over the business. Successful data projects are a partnership between the project team and key business users who work with the numbers on a daily basis. Don’t expect that a diktat from the 17th floor is going to be enough to drive them into making this thing a success, it’s your job to involve as many key players as possible, make them feel they’re being listened to and that they have some control over the direction of the project. 

Throughout the course of any data project, key business users should have frequent and regular opportunities to provide feedback. This agile approach will help to ensure that the solution is actually what the business wants – unless they are able to see the solution in action it’s impossible for them to really know what they want! An added bonus is that they will feel that they have shaped the project and will have a vested interest in the outcome. 

Recoup your investment 

From the C-Suite down to the office floor, what everybody wants is something that makes their work easier and the business more successful. If you can demonstrate that what you are doing is going to achieve tangible results they will sit up and listen. For example, a report which currently takes 5 hours will take 1 hour as a result of this project. And if that report is created by 100 people at a cost of £50 per hour, the bill drops from £25,000 to £5,000. 

To hammer that point home, McKinsey carried out analysis over a five year period which showed that companies who put data at the heart of their operation enjoyed marked improvements across all departments, with sales and marketing ROI increasing by 15%-20%. Investing in creating a data driven culture is vital for the growth of any business determined to stay ahead of the pack. 

6 data experts you need in your project team

Posted on by David Rice

Picture this: you’ve decided to embark on an analytics project and find yourself in the offices of an experienced analytics team. To the untrained eye it might look like a bunch of people in comic book t-shirts staring into seemingly infinite streams of mysterious numbers, symbols and letters.

What are they all doing? You might well ask! We’re the first to admit that data analytics is hardly the most accessible business. With that in mind, here is a handy cut out and keep guide to the different types of people you want to work on your data.

Business analyst, aka the Go-between

One of your main points of contact on any project, the first thing you’ll notice about the business analyst is that they speak a language you understand. This is because the role isn’t explicitly technical, in fact some people believe it’s better for them to be focussed solely on business needs. It’s still really important that they do have a good working knowledge of the data so they can understand and represent all parties and be able to explain in comprehensible terms the possibilities and limitations of what we can deliver.

Solution architect, aka the Overseer

Like a bricks and mortar architect, this person is responsible for producing the blueprint for your project and setting out a workable solution from end-to-end. To expand the building analogy, they also take on some of the duties of a site manager, deciding on the tools we will need to use, such as AI or machine learning. The solution architect is the lynchpin, connecting everyone involved in the project and providing you with an overview.

Data modeller, aka the Translator

This person translates different raw data sets into accessible formats so that it can be usefully queried in order to provide the answers your business needs. Data modellers use the context and knowledge of the business provided by the Business Analyst to design how the data is stored, making complex data accessible and understandable for end users in the business.

Data engineer, aka the Wrangler

Every team needs someone who’s good at bringing things together. The data engineer (once known as the ETL developer) extracts the data from several often complex systems and wrangles it, filters it and loads it into a user friendly and accessible data model – designed by the data modeller – that your business users and data scientists will understand. The data engineer needs great communication skills as they have to understand what it is your business wants to get out of the finished database and ensure that the solution provided meets those expectations.

Data storyteller, aka the Visionary

Previously known as a data analyst, a bit of a dry moniker for someone who can visualise data and produce reports that are easily understood by people with little knowledge of analytics. A good storyteller turns data analyses into meaningful, understandable and actionable insights that will benefit your business.

Data scientist, aka the Prophet

So, data analytics has provided the initial actionable insights for your business, but what if you want more? The data scientist is your new best friend, looking even deeper into the figures for untapped findings, identifying new correlations and making your data work harder. 

Finally, let’s not forget the invaluable input of the project managers who keep the whole thing on the road and the vital role of the experts within your business. At Snap Analytics we take an integrated approach, connecting our expertise across the different data roles with your business experts. Working closely together we will help you to gain new insights from your data in order to make better and more informed decisions.

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