Quite often, businesses will embark on a project to replace a business-critical piece of software, usually based on the need of specific functionality and/or compliance. However, it is just as often that there is a tunnel-vision approach, and an opportunity is missed to re-evaluate the way in which data is collected for analysis.
Data is an invaluable resource for businesses today. It is well-known that there is value in the information, but due to high volumes and difficulties in collecting, organising and relaying it, unlocking that value can be a challenge in itself.
It’s not unusual that a business’s current process for analysing data is inefficient and labour intensive; a spreadsheet for this, a spreadsheet for that; lots of manual input after referring to dozens of reports from numerous systems.
Developing a data strategy can aid a business in overcoming these roadblocks, and what better time to do this than when they’re looking to replace a system (or multiple disparate systems). Taking advantage of this time, a savvy project sponsor can grant access to the true value of their collected data, whilst still maintaining efficiency from their resources. And let’s not forget, they’re now implementing a system which will give the business more than just the functionality they were after; they’re gaining invaluable insight into their business. It’s a win-win situation.
So, “What is a Data Strategy?” I hear you say, and how does it relate to Enterprise?
Well, the MIT CISR Data Board defines it as “a central, integrated concept that articulates how data will enable and inspire business strategy”. In more layman terms, it simply means a foresight into how the company will collect, store, manage and use data.
In an Enterprise solution you’re gathering a lot of data, there’s no doubt about that, but you do need to question whether your collecting all the data you need, or if some of the data you’re collecting is actually relevant and/or useful. Every business is different, having their own little nuances, and therefore it’s pretty fair to say that each organisation’s data strategy will be different too. That said, they will all generally do the following:
- Define how the data will help the company meet its business goals.
- Lay out how the company will complete the desired data activities to achieve its objectives.
- Describe the changes the organisation needs to make to maximise the value of its data activities and outline plans for how the company will make those changes.
- Establish a timeline for the completing the proposed activities, define the milestones and priorities and describe a strategy moving forward.
- Discuss the financial justification of the suggested data activities and how the company will benefit from them, and use the insight to increase its profits and monetise its data.*
*This is probably the most important point when you come to put a data strategy proposal together and get buy-in.
How does one go about building a Data Strategy? This can generally be broken down into 7 steps:
1. Get buy-in by creating a proposal
Before you embark on building your data strategy, you need to earn buy-in across the organisation. Executive buy-in is crucial, as this will release the resource and/or funds you require. You’ll also need buy-in from other levels to ensure you receive the necessary participation for the implementation to be a success.
Getting the buy-in from the leadership team will require you to show how the strategy will benefit the company; this will comprise of economic logic (we’ll save X amount of man hours per week and therefore X amount of money and/employee time can be invested elsewhere).
2. Put a Data Management Team in place
Once you’re received approval, you’ll want to create a data management team. You’ll probably want to include senior managers and department heads you approached to get buy-in, and cement that by giving them ownership of specific areas; this will greatly improve the results as they will have a better understanding of the value of the data and the challenges that are likely to present themselves in that they may face.
3. Identify the data you want/need and decide where it’ll come from
Next, you’ll need to determine what do you want and how you’re going to get it. For example, the Sales Director would like to focus their Sales Team on the more profitable markets that the business sells into. Ideally, a readily available ‘Sales by Market’ report should be available to help identify where the focus should lie. Similarly, the Marketing Director needs identify the markets that require their profile raised and to run focused campaigns. One report, two birds!
4. Set goals for data collection and distribution
There’s little point in having a data strategy if there are no specific and measurable goals. Proof is, ultimately, in the pudding. How many more leads have been generated in the markets targeted by the new campaigns? Have you seen a percentage increase in sales since the Sales Team shifted focus?
Develop both short and long-term goals that apply to the individual task and departments. Just because no new leads are generated by the campaigns in the first quarter, it doesn’t mean that the data collected is useless and should be binned; the Sales Team have seen 80% increase in turnover from using the data to focus their energies.
Perhaps you simply need to look at the types of campaigns that are seeing more success and change tact, and this is something you’ve hopefully included in the wider data strategy you’re already monitoring and reporting on. As part of the Marketing Teams long-term goals, we may see more leads in the later half of the fiscal year and, therefore, the data has been useful.
5. Build a data strategy roadmap
You’ve already created your goals, so you’ll need to outline how you plan to achieve them. How are we going to produce a Sales by Market report? We need to record the market the customer is in. How are we going to collect that data? Use the SIC codes available from Companies House, ask customers for this data and populate the relevant field on the customer record in the ERP solution.
This is your roadmap for your data strategy. As your project progresses, it is important for you to regularly evaluate what’s working well, and what’s not. For example, account managers aren’t having much success in contacting customers and obtaining SIC codes, but the junior Marketing Exec has managed to update 50% of your customer database in a few short days by using Companies House.
6. Data storage and organisation planning
The strategy should include policies to data storage and organisation. If the goals you have set out to achieve are to be reached, then collection of data might be mandatory and that might be easier to adhere to if, say, it’s only possible to create a new customer record if that mandatory data is populated; if there’s no method to get around it, it will be followed.
Data storage is a relatively simple technology capability; you just need to decide where to store it, how much storage capacity you’ll need and how easy is it to access. In the example given above, the data would naturally sit within the ERP database, the data footprint this causes will be minimal to insignificant to the existing database size, and also readily available for reporting by utilising the Business Intelligence tool already in place.
Ultimately, your goal in creating a data storage and organisation plan is to make your data accessible, shareable and actionable for the parties that may need it. Different companies will often have different approaches, but a general rule is that you should store your data in an easily accessible system in a consistent format.
7. Gain final approval and implement the data strategy
Once you’ve ticked off the other 6 steps, you can roll your data strategy up into a business plan and present it to the executives for final approval. This will list all the strategies you’ll use to achieve the company’s data related objectives, and resources you’ll need to implement the strategy, including capital investments, new hires, new processes, etc.
Once signed off, you can begin implementing your new data strategy. As previously mentioned, this should be closely monitored and reviewed as an ongoing process, making sure that you’re still aligning to your goals and make any adjusts as required.
Need help with your data strategy? Contact us to discuss your requirements.
Katie Mansell
