#6 Let’s create an implementation plan

This blog is one of an eight-part series of blogs – read our introduction to see how this blog fits into the series.

OK, let’s make this happen! The most important thing at this stage is to create an implementation plan that is clear and understandable, maps out the stages of development, and identifies resources required to deliver the plan. And this is where most strategies get a bad name, by not converting ideas into actions and delivery. But not this time! We need to ensure that the implementation plan we create sets the business up to succeed. 

Where do we begin?

Everything feels complex when you try to do it all in one go. And you can’t do everything at once. So, we’re big fans of breaking down projects into a series of manageable chunks, and specific phases of work. But how do we break the work up in a way that is efficient, logical, and cost-effective?

There are several ways we can split a project into phases – we can:

• Prioritise one business area at a time – for instance, we could do Finance, then Sales, then Marketing
• Prioritise a data source at a time – for instance, there could be 1-2 data sources which are commonly used across the business, and we could start with these ones first
• Prioritise a business challenge or opportunity first – for instance, we could create a Board-level report first, or a report that supports cross-selling and upselling activity across different regions/products/teams

Whichever one you choose; we usually create a plan that looks something like this:

• 1^st quarter 
  • Set up the selected technology stack and BI tools
  • Connect the prioritised data source/s
  • Create the prioritised business reports
• 2^nd quarter
  • Connect the next prioritised data source/s
  • Create the next prioritised business reports
• And so on for each month/quarter

This approach means that everyone knows what’s prioritised, what’s expected, and by when.

Data projects are, by their nature, cross-functional, cross-departmental, and cross-regional. So, you’ll need a business-wide approach to data governance. Data governance issues could include:

• Deciding on business priorities and the phases of work
• Defining the business logic and business rules for master data and unique identifiers
• Confirming the business ownership for data sources and reports
• Selecting the technology stack and data tools to be used across the business

We often recommend setting up a Data Working Group to jointly own all decisions relating to data across the business. The Data Working Group needs to be sponsored by someone at Board level – someone to champion the commitment to data across the business, and ideally the CEO. 

Who do we need on the team?

No one data expert can do everything when it comes to data. Different data experts are great at different things. And no-one is great at everything. So, you’ll need a mix of data skills across the team, including:

1. Data consultant – someone to create, own and develop the data strategy, and ensure that the strategy delivers new commercial and competitive advantage for the business
2. Data architect – someone to design, develop, build, and support the technology stack and to configure, maintain and develop the selected data tools
3. Data engineer – someone to extract the data from the original sources, combine the data together, and prepare it for modelling and analysis
4. Data visualiser – someone to transform the data into intuitive, clear dashboards, reports, and graphs
5. Data scientist – someone to design, develop, build, and support statistical models to identify new patterns and trends

Some of these roles you might want in-house, particularly where you’re likely to need these skills every day – such as the data engineer and data visualiser. Some of these roles you might want to outsource to an external data consultancy, as you won’t need these roles full-time, just now and again – such as the data consultant, data architect and data scientist.

When filling these roles, you should consider the potential to develop people in-house, compared to recruiting new roles, compared to outsourcing these roles, or bringing in part-time roles. All have pros and cons.

This is a tricky question to answer but it helps to break down the costs into the types of costs you’ll need to consider, including:

1. Setup fees – these fees will depend on whether you setup your technology stack in-house, and use existing resources, or outsource this work to a data consultancy. Depending on the scope of the project, these fees could range from £10,000-£100,000+.
2. Ongoing licence fees – these fees are paid to third parties and the amount will depend on which tools you select for ETL, data warehousing, and BI tools. Depending on the tools selected, the configuration of these tools, and the volumes of data processed, these fees could range from £100-£2,000+ per month.
3. Ongoing support fees – these fees will depend on how much support you bring in from your data consultancy but could range from £750-£1,250 per day.

Every project is different.  Every business is different. So, every budget is different.

What timeline is realistic?

Again, a tricky question, as it will entirely depend on the scope of work. But, as a guide, we often see the first phase of a data project being completed within 2-3 months, so the business can see an end-to-end process from data collection to data modelling, to data reporting, for the prioritised business process. For many businesses, to take up and running with data integration across the business, can often take approximately 12 months.

Now that you have created an implementation plan, it’s time to consider the culture change that may be required to become data-driven. So, check out our next blog in this series for some simple tips on how to bring everyone on the journey with you to deliver a data transformation.

Do YOU need an independent, objective review of your implementation plan?

Well, you’re in the right place. We can run the Discovery & Design programme for your business. The benefits of outsourcing to us are:

1. OBJECTIVITY – we bring a fresh pair of eyes to your business and we’re unhindered by office politics, historical decisions, and legacy systems
2. INDEPENDENCE – we’re technology-agnostic, so we can give you an independent view, with no vested interest in you selecting, or staying with, a certain vendor, tool, or platform
3. AWARD-WINNING DATA CONSULTANTS – we’ve done this before…for 75+ projects and for 50+ businesses, so we can bring our wider experience to the mix

When we run a Discovery & Design programme for one of our clients, it typically takes 4 weeks, depending on the scope of the project. Most businesses want results quickly and simply…so that’s what we do – we worry about the complexity, so you don’t have to.

Find out more at https://datacubed.nz/services/.