Get Your Data Strategy On Board
Only 32% of UK organisations plan to significantly invest in data and analytics in 2017, according to new research by DataIQ Leaders.
In the same study three out of ten organisations claim they are either reaching maturity or are already advanced in their adoption of data and analytics.
It can typically take three to five years to build out a data organisation and embed the use of analytics into an organisation. This means those 30 per cent have a significant competitive advantage but 70% don’t.
So why has data analytics not been prioritised sooner? A recent study by Accenture found 89% of business leaders think big data will transform businesses as much as the Internet did. Most organisations have distinct business and IT strategies. With data now recognised as being crucial to the success of a business, a clear data strategy is now also just as important.
But what does a coherent data strategy look like? And how do you get the decision makers like your CEO, CMO, COO and fellow corporate executives to move from reading about data analytics and data science to actually investing in it?
How to get Executive Buy-In
Acknowledge that board buy-in will be hard, most organisations are only just starting to appreciate the value of data and what it can achieve, so don’t despair because you’re not alone.
The good news is that with persistence and a clearly defined data strategy in place you can present a persuasive argument to win your corporate executives.
Firstly, identify and do your homework on the executives you need to get on board. Find out their leadership styles and motivators, find out what challenges they’re working on. Regardless of the department, whether it is sales or marketing, senior executives are always concerned about people, money, and time.
Study and understand the strategic aims of your organisation. Your senior personnel will be working towards these aims. Your chance of success is much greater if you can prove your data strategy aligns to the business objectives, and addresses the key business problems or needs.
Secure a 30-minute meeting with every executive who might be impacted by the data strategy initiative and excite them with a one-on-one conversation that highlights the benefits of what your strategy aims to achieve. Identify how the strategy will solve an organisational challenge or provide an opportunity. This gets them enthusiastic about the outcome and makes them more likely to commit to the initiative.
If you can, try and get a senior sponsor. Your proposal will be far more credible if a respected figure champions it.
When putting forward your Proposal
Talk plain and unpretentious English, not jargon. Senior executives aren’t fussed about the proposal’s technical specifications – they just want to understand the costs and outcomes.
With that in mind, focus on the benefits, not the features of your project. Senior management are ultimately only interested in what the project can do for the business. Emphasis the value and qualify the ROI, not the costs.
Don’t just show up with an Excel document with a million rows of data. Use tools and presentation formats that are simple but impactful, make sure you illustrate your points with visual examples.
Demonstrate how your proposal will place you ahead of your competitors (which will always get senior personal sitting up and listening).
Executives respond well to facts and figures, so make sure you include these in your presentation and share a deck with each executive. If possible, modify each one to the specific pain-points of their respective departments.
Break down your plan down into plain and manageable bite size chunks, focus on one thing that a time. Start small but focus on long-term value, data programs take time to grow and you will need to stress this to the board. When results aren’t seen for a long time, enthusiasm and commitment can diminish.
Therefore, the short-term wins are vital. Draw attention to the areas where you can achieve early wins and quick returns, this will build your projects credibility. A foreseeable success will make your executives more likely to buy into your overall strategy, so set milestones and communicate when you pass them.
Again, your proposal should not only be simple and highly visualised, but it should also clearly communicate everyone’s role so they feel like they have an important connection and commitment to the project. Emphasis the implications for everyone, spell out the next steps which each person will need to take clearly: this will avoid presenting an ambiguous picture that results in nothing moving forwards.
What should your data strategy look like?
What are the components good looking and healthy data strategy? Start by asking yourself these to two questions: “Where is the money?” and “Where can I have a tangible impact?”, these will give you a good idea of where to start your project. Then begin to map out the following:
Your background and context:
This section of your proposal should define the reasons that demanded a data strategy in the first place, and where you’re going to make an impact. It could be a corporate strategic direction or a digital transformation initiative.
Your business case:
The aim of a data strategy is to provide business value and this section should demonstrate the value which will be unlocked both through quantitative and qualitative analyse. How will this help to advance your organisation? Remember the primary purpose of your data strategy should be to unlock business value by leveraging data.
Your goals:
What are you trying to achieve? The data strategy must compliment the business strategy otherwise you’ll never get it on board. This section should articulate the specific data strategy related goals - ideally in a SMART fashion (Specific, Measurable, Agreed upon, Realistic, Time-based).
Your implementation journey:
What data do you need where and when? Today and in the future? What level of data quality is necessary? This section connects the strategy with tactics and gives your decision makers a roadmap on how the strategy will be implemented over a specific time period. It should highlight the following:
- Data collection and categorisation. What data is necessary to meet your business goals? How often does it need to be updated? What data archiving requirements are there?
- Data integration. How should data be shared between the various data silos? This is often where things go wrong. The need to “join the dots” means data connections are becoming as important as data collections. How do you integrate data silos? What data transfers are necessary and how frequently? How do you track cross channel? What tags are you using and do you need to standardise?
- Data storage and technology. How to access, share and manage data? Some data may need to be available in real-time whereas other data may not be as time critical. Should it be a SaaS or in-house solution? Where is your database of record for different data and do you require a single customer view?
- Data governance, protection and security. Probably the least sexy part of the strategy, but the most vital. The business will need to define the roles and responsibilities, approvals and workflows. Ask yourself how much is the data worth? Putting a value on data helps to make data management a continuous improvement process.
Your risks and success factors:
Define what you want to accomplish and identify the risks which will stop you from succeeding. Your data strategy should directly address various risk factors and success enablers (or accelerators). Change management is either a major risk or success if not thought through in detail so make sure to address it head on.
Your estimated budget:
There are going to be costs, but be as realistic, transparent and comprehensive as possible. If you hide a few truths to get your strategy approved faster, it will only hurt you later.
Your Key Performance Indicators:
You can’t manage what you can’t measure. To ensure that your strategy is either on track or if needs to be adjusted, identify the KPIs that need to be tracked on a short and long term basis.
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